with a unique id (e.g. ch02), data-chapter-index, data-topic (slug), and data-title (human-readable). Dataset Each dataset is a

with a unique id (e.g. dataset-grit-sample-size-grit-wave), data-chapter, data-dataset-title, and data-report-title. Deep-link via https://www.greenbook.org/grit#[dataset-id]. Design, Methodology & Sample This section explains how the GRIT process is designed, what the final sample looks like, and how the report is structured, including key segments, labels, and definitions. WHAT IS THE GRIT REPORT? [ORIENTATION] RELABELING PAST GRIT PAST WAVES [ORIENTATION] WHAT’S NEW IN THIS REPORT [DATA] THE FINAL SAMPLE [DATA] GRIT SAMPLE SIZE: GRIT WAVE All Sample Brand Supplier Other Industry Participants 14AB 1,919 497 1,422 0 15A 1,865 355 1,429 81 16A 1,497 330 1,167 0 16B 2,144 471 1,673 0 17A 1,583 312 1,227 44 17B 2,942 647 1,990 305 18A 1,533 331 1,182 20 18B 3,930 981 2,949 0 19A 1,260 329 931 0 19B 2,880 844 2,036 0 20A 1,117 298 790 29 20B 2,098 366 1,615 117 21A 1,071 274 769 28 21B 3,242 875 2,325 42 22A 1,323 254 1,002 67 22B 2,701 402 2,275 24 23A 985 232 731 22 23B 2,100 332 1,753 15 24A 1,035 385 628 22 24B 2,291 500 1,781 10 25A 992 379 598 15 25B 2,441 620 1,802 19 26A 735 328 387 20 Takeaway: GRIT collects robust sample from brand- and supplier-side professionals to represent industry demand as well as what the industry offers. Source: GRIT 2026 Insights Practice Report, Greenbook GRIT SAMPLE SIZE: GRIT SEGMENT Brand Research 176 Analytics 152 Supplier Tech-led 39 Service-led: ≤20 FTE 158 Service-led: 21-100 FTE 79 Service-led: 101-500 FTE 56 Service-led: 500+ FTE 55 Takeaway: Sizes of GRIT’s new segments range from 39 to 158. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. SAMPLE ADJUSTMENT [ORIENTATION] GRIT SAMPLE SIZE: REGION Brand Supplier North America 179 229 Europe 87 78 Asia-Pacific 45 46 South & Central America 8 18 Africa & Middle East 7 14 Multi-region or undefined 2 2 Takeaway: North America is the most prominent regional contributor, followed by Europe and Asia-Pacific. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PARTICIPATION ACROSS GLOBAL REGIONS: LAST FIVE INSIGHTS PRACTICE WAVES (BRAND) 22A 23A 24A 25A 26A North America 61% 62% 63% 63% 64% Europe 24% 27% 25% 25% 22% Asia-Pacific 8% 6% 6% 6% 9% Africa & Middle East 4% 2% 2% 3% 2% South & Central America 2% 3% 4% 3% 2% Multi-region or undefined 1% 1% 0% 1% 1% n = 254 402 385 379 328 Takeaway: Across waves, North America has been the most prominent regional contributor on the brand side, followed by Europe and Asia-Pacific. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PARTICIPATION ACROSS GLOBAL REGIONS: LAST FIVE INSIGHTS PRACTICE WAVES (SUPPLIER) 22A 23A 24A 25A 26A North America 51% 49% 49% 48% 50% Europe 26% 26% 26% 25% 24% Asia-Pacific 16% 16% 16% 16% 17% South & Central America 3% 5% 5% 5% 4% Africa & Middle East 4% 3% 3% 3% 3% Multi-region or undefined 0% 1% 1% 2% 1% n = 1,002 731 628 596 387 Takeaway: Across waves, North America has been the most prominent regional contributor on the supplier side, followed by Europe and Asia-Pacific. Source: GRIT 2026 Insights Practice Report, Greenbook. EXPERIENCED GRIT PARTICIPANTS [DATA] YEARS IN ROLE RELATED TO INSIGHTS, ANALYTICS, OR RESEARCH: GRIT SEGMENT 2 years or less 3 to 5 years 6 to 10 years 11 to 15 years 16 to 20 years More than 20 years Brand (n = 328) 2% 10% 19% 25% 12% 32% Supplier (n = 387) 3% 8% 12% 11% 10% 56% Takeaway: Very few brands (2%) and suppliers (3%) have two years or fewer experience, and most suppliers have more than 20 years (56%). Source: GRIT 2026 Insights Practice Report, Greenbook ROLE IN STRATEGIC DECISIONS: GRIT SEGMENT Make decisions Influence decisions Member of a team Do not formally influence Brand (n = 328) 14% 49% 22% 15% Supplier (n = 387) 34% 33% 22% 10% Takeaway: More than 60% of brands (63%) and suppliers (67%) make or influence strategic decisions. Source: GRIT 2026 Insights Practice Report, Greenbook GRIT DATA QUALITY ASSURANCE [ORIENTATION] DIFFERENCES FROM LAST YEAR [ORIENTATION] TAILORING FOR AI READERS [ORIENTATION] THE BIG PICTURE [STRATEGIC INTERPRETATION] The 2026 GRIT Insights Practice Report presents industry-trend data for readers to interpret according to their own experience and needs; the perspectives GRIT offers are aids to thinking through implications, not definitive claims, and few findings can be stated with certainty. This edition adopts the supplier segmentation introduced in the 2025 Business & Innovation Report — tech-led versus service-led, with service-led stratified by full-time employee count — intended to let participants identify their own segment more readily than the prior revenue-source framework. GRIT has long functioned as a forum for differing perspectives while presenting data neutrally, leaving conclusions to the reader. Understanding the design, methodology, and sample composition is what lets a reader separate established fact from hypothesis and judge which trends are meaningful for their own context. Full methodology, sample, and definitions: GRIT 2026 Insights Practice Report. Industry Buzz Topics Each year, GRIT asks insights professionals which topics they follow most closely and why to identify which topics have the most “buzz.” WHAT HAS THE INSIGHTS INDUSTRY BUZZING? [ORIENTATION] 2026 BUZZ TOPICS MAJOR THEMES MINOR CHORDS AI Data quality & fraud Data & analytics Industry & workforce trends Consumer & market insights Privacy/regulation/governance Methods Behavioral & social science Synthetic data & personas Marketing measurement Specific verticals Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. TOP THREE BUZZ TOPIC THEMES: GRIT SEGMENT Brand: Research Brand: Analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE AI 54% 45% 54% 54% 53% 55% 38% Consumer & market insights 15% 20% 8% 14% 3% 22% 26% Methods 15% 7% 9% 21% 23% 16% 16% Synthetic data & personas 14% 5% 25% 11% 15% 28% 9% Data & analytics 11% 30% 29% 15% 19% 21% 28% Data quality & fraud 2% 2% 12% 21% 17% 3% 5% n = 101 121 20 70 31 19 19 Green shading indicates top three areas led by segment. Takeaway: AI is the leading buzz topic in each segment, although only mentioned by minorities among brand-side analytics professionals (45%) and service-led suppliers with 500+ FTE (38%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. AI [DATA] AI SUB-TOPICS AI (General) AI Impact on Industries & Workflow Wariness About AI AI & the Research Process AI & Analytics Generative AI/LLMs Agentic AI/Automation AI Tools & Platforms Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. AI | GENERAL [DATA] AI Impact on Industries & Workflow Wariness About AI AI & the Research Process AI & Analytics AI | GENERATIVE AI/LLMS [DATA] AI | AGENTIC AI/AUTOMATION [DATA] AI | AI TOOLS & PLATFORMS [DATA] DATA & ANALYTICS [DATA] DATA & ANALYTICS SUB-TOPICS Analytics tools/platforms/BI Insight activation/storytelling Data visualization & reporting Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. DATA & ANALYTICS | ANALYTICS TOOLS/PLATFORMS/BI [DATA] DATA & ANALYTICS | INSIGHT ACTIVATION/STORYTELLING [DATA] DATA & ANALYTICS | DATA VISUALIZATION & REPORTING [DATA] CONSUMER & MARKET INSIGHTS [DATA] Consumer Behavior & Trends [DATA] Market & Competitive Intelligence [DATA] Brand & Product Research [DATA] METHODS [DATA] METHODS SUB-TOPICS Mixed/emerging methods Quantitative methods Qualitative methods Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. METHODS | MIXED/EMERGING METHODS [DATA] METHODS | QUANTITATIVE METHODS [DATA] METHODS | QUALITATIVE METHODS [DATA] SYNTHETIC DATA & PERSONAS [DATA] SPECIFIC VERTICALS [DATA] DATA QUALITY & FRAUD [DATA] INDUSTRY & WORKFORCE TRENDS [DATA] PRIVACY/REGULATION/GOVERNANCE [DATA] BEHAVIORAL & SOCIAL SCIENCE [DATA] MARKETING MEASUREMENT [DATA] BUZZ TOPICS | BRAND POV [DATA] BUZZ TOPICS – MAJOR THEMES (BRAND) Research Analytics AI 54% 45% Consumer & market insights 15% 20% Methods 15% 7% Synthetic data & personas 14% 5% Data & analytics 11% 30% Specific verticals 7% 18% n = 101 121 Takeaway: Brand-side analytics professionals are more likely than researchers to closely follow “Data & Analytics” (30% to 11%) and “Specific Verticals” (18% to 7%); researchers are somewhat more likely to follow “AI” (54% to 45%) and “Methods” (15% to 7%). Source: GRIT 2026 Insights Practice Report, Greenbook BUZZ TOPICS – MINOR CHORDS (BRAND) Research Analytics Industry & workforce trends 7% 0% Privacy/regulation/governance 3% 7% Data quality & fraud 2% 2% Marketing measurement 2% 2% Behavioral & social science 1% 2% n = 101 121 Takeaway: Brand-side researchers may be more likely to closely follow “Industry & Workforce Trends” (7% to 0%); analytics professionals may be more likely to follow “Privacy/Regulation/Governance” (7% to 3%). Source: GRIT 2026 Insights Practice Report, Greenbook BUZZ TOPICS | SUPPLIER POV [DATA] BUZZ TOPICS – MAJOR THEMES (SUPPLIER) Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE AI 54% 54% 53% 55% 38% Data & analytics 29% 15% 19% 21% 28% Consumer & market insights 8% 14% 3% 22% 26% Methods 9% 21% 23% 16% 16% Synthetic data & personas 25% 11% 15% 28% 9% Specific verticals 8% 9% 15% 0% 8% n = 20 70 31 19 19 Takeaway: “AI” is the most frequent theme in each supplier segment, and it is mentioned by a majority of every segment except service-led suppliers with 500+ FTE (38%). Source: GRIT 2026 Insights Practice Report, Greenbook. BUZZ TOPICS – MINOR CHORDS (SUPPLIER) Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Industry & workforce trends 5% 5% 8% 13% 9% Data quality & fraud 12% 21% 17% 3% 5% Marketing measurement 8% 0% 5% 0% 5% Behavioral & social science 0% 8% 3% 5% 0% Privacy/regulation/governance 0% 5% 3% 0% 0% n = 20 70 31 19 19 Takeaway: Although considered a “minor chord” overall, “Data Quality & Fraud” seems more like a major theme among service-led suppliers with ≤20 FTE (21%) and with 21 to 100 FTE (17%). Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC INTERPRETATION] 2026 MAJOR THEMES 2025 MAJOR THEMES AI AI & machine learning Data & analytics Data analytics & Data Science Consumer & market insights Brand, marketing, & customer insights Methods Research methods & tools Synthetic data & personas [Not a major theme] Specific verticals Industry-specific trends [Minor Chord] Data quality & integrity Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. The 2026 buzz topics resemble 2025’s, but the conversation within them has matured. AI remains dominant yet is no longer a binary adopt-or-not debate; participants are asking which kind — generative, agentic, tool-based — for which purpose and with what safeguards. The emotional temperature has cooled even as the stakes have risen. A consistent split runs through every AI sub-topic between those watching AI (evaluating tools, tracking developments) and those deploying it (redesigning workflows, building agentic systems), with the agentic group a clear vanguard. Synthetic data has crossed into major-theme status, drawing the kind of active, sometimes anxious evaluation AI itself attracted in 2024–25. Beneath the topics runs an anxiety about whether insights work is valued and trusted — less “will AI take my job” than “does my organization believe in what I do.” Segment differences are pronounced, and lower mention rates can mask deeper engagement: brand-side analytics professionals and large service-led suppliers are among the least likely to name AI, yet arguably the most engaged with it, as familiarity may suppress explicit mention. (Those most alarmed by job loss may no longer be in the sample.) Full analysis and supporting data: GRIT 2026 Insights Practice Report. Brand-side Roles & Teams This section discusses how brand-side roles differ across market research and analytics professionals and the distinct corporate profiles that tend to be associated with each. ARE INSIGHTS ROLES CONVERGING? [ORIENTATION] PRIMARY ROLE OF INSIGHTS PROFESSIONALS: BRAND SEGMENT In-house research Insights operations Strategic insights consulting Data analysis/modeling Research outsourcing CX/UX/VoC Other Research (n = 175) 32% 25% 24% 8% 6% 3% 2% Analytics (n = 152) 6% 32% 9% 33% 0% 20% 0% Takeaway: Most brand-side researchers are concentrated in in-house research (32%), insights operations (25%), and strategic insights consulting (24%); analytics professionals are primarily in data analysis/modeling (33%) and insights operations (32%), with notable representation in CX/UX/VoC (20%). Source: GRIT 2026 Insights Practice Report, Greenbook SIGNIFICANT ROLES FOR PEOPLE WHO PRIMARILY FOCUS ON INSIGHTS (BRAND) 26A Wording 25A Wording Customer/user feedback or (VoC) programs “Voice of the Customer or Consumer” (VoC) In-house data analysis or modeling Data analysts In-house research provider to internal clients In-house research provider to internal clients Insights, analytics, or research operations [not included] Research outsourcing or supplier management Research outsourcing Strategic insights consulting or advisory Strategic insights consultants Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ROLE DIFFERENCES | BRAND POV [DATA] KEY ACTIVITIES: BRAND SEGMENT Research Analytics Manage/conduct/commission research 86% 61% Report/communicate/implement insights findings 89% 67% Acquire/adopt platforms or tools for research/analytics 71% 64% Provide non-research services to insights professionals 8% 6% Manage/conduct/commission modeling or analytics 44% 81% Other activities related to insights 72% 36% n = 175 152 Takeaway: Brand-side analytics professionals are more involved in modeling and analytics work (81% to 44%), but roles that skew toward researchers have smaller gaps. Source: GRIT 2026 Insights Practice Report, Greenbook KEY CHARACTERISTICS OF RESEARCH SEGMENT: BRAND SEGMENT Research Analytics Staff’s primary role: in-house research 32% 6% All insights professionals in a formal group 52% 14% n (range) = 158-175 147-152 Takeaway: Brand-side researchers are more than five times as likely as analytics professionals to say in-house research is the primary role for insights professionals on staff (32% to 6%), and nearly four times as likely to say all insights professionals work within a formal research or insights group (52% to 14%). Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPES WORK WITH REGULARLY: BRAND SEGMENT Research Analytics Technology 62% 72% Full-service research 52% 27% Qualitative research 45% 41% Data & analytics 43% 70% Field services 34% 24% Strategic consultancies 20% 38% n = 176 152 Takeaway: Both brand-side segments rely heavily on technology suppliers, but researchers are nearly twice as likely to work regularly with full-service research (52% to 27%), while analytics professionals are more likely to engage data and analytics (70% to 43%) and strategic consultancies (38% vs. 20%). Source: GRIT 2026 Insights Practice Report, Greenbook KEY RESEARCH FOCUS: BRAND SEGMENT Research Analytics CPG is a significant market 25% 16% All work is B2C (no B2B) 22% 3% Most insights work is B2B 38% 54% Financial services is a significant market 26% 38% n (range) = 162-164 141-147 Takeaway: Brand-side analytics professionals are more likely to focus on B2B work (54% to 38% say it’s most of their work) and financial services (38% vs. 26%), while researchers are more likely to work in CPG (25% to 16%). Source: GRIT 2026 Insights Practice Report, Greenbook CURRENT USE OF AGENTIC AI: BRAND SEGMENT Research Analytics Creating/updating reports, dashboards, etc. 50% 71% Preparing and integrating data 43% 73% n = 88 77 Takeaway: Brand-side analytics professionals are substantially more likely than researchers to currently use agentic AI for both creating/updating reports (71% vs. 50%) and preparing and integrating data (73% vs. 43%). Source: GRIT 2026 Insights Practice Report, Greenbook YOUR DEPARTMENT OR FUNCTIONAL AREA (BRAND) 26A Wording 25A Wording Analytics or Data Science Analytics Customer Experience (CX) or VoC [not included] Executive team Executive team Insights or research group Insights or research group Marketing, brand, or communications Marketing Product, User Experience (UX), Innovation, or R&D Product management R&D Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PARTICIPANT DEPARTMENT/AREA: BRAND SEGMENT Research Analytics Insights or research group 67% 13% Marketing, brand, or communications 12% 10% Product, UX, Innovation, or R&D 8% 10% Analytics or Data Science 4% 52% Executive team 3% 10% CX or VoC 3% 2% Other 3% 4% n = 175 152 Takeaway: Most brand-side research professionals are situated in insights or research groups (67%), while most analytics professionals are in analytics or Data Science departments (52%). Source: GRIT 2026 Insights Practice Report, Greenbook DEPARTMENT OR FUNCTIONAL AREA: GRIT WAVE (BRAND: RESEARCH) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Insights or research group 53% 58% 58% 70% 67% -3% Marketing, brand, or communications 22% 20% 11% 14% 12% -2% Product, UX, Innovation, or R&D 6% 7% 16% 5% 8% +3% R&D 3% 4% 11% 5% N/A N/A Product management 3% 3% 4% 0% N/A N/A Analytics or Data Science 6% 3% 9% 3% 4% +1% Executive team 4% 5% 4% 3% 3% -- CX or VoC N/A N/A N/A N/A 3% N/A Other 1% 0% 4% 5% 3% -2% n = 254 211 191 202 175 Takeaway: The share of brand-side researchers in insights or research groups has grown from 53% in 22A to 67% in 26A, while marketing, brand, or communications representation has declined from a high of 22% (22A) to 12% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PARTICIPANT DEPARTMENT/AREA: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Analytics or Data Science 27% 40% 46% 52% +6% Insights or research group 10% 10% 18% 13% -5% Product, UX, Innovation, or R&D 17% 15% 10% 10% -- R&D 8% 10% 7% N/A N/A Product management 9% 5% 3% N/A N/A Marketing, brand, or communications 27% 12% 9% 10% +1% Executive team 6% 12% 11% 10% -1% CX or VoC N/A N/A N/A 2% N/A Other 12% 10% 6% 4% -2% n = 183 194 177 152 Takeaway: Brand-side analytics professionals in formal analytics or Data Science departments have grown from 27% in 23A to 52% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. MOST SIGNIFICANT ROLES | BRAND POV [DATA] ALL SIGNIFICANT INSIGHTS PROFESSIONAL ROLES: BRAND SEGMENT Research Analytics Research – analytics Insights operations 82% 83% -1% In-house research 68% 56% +12% Data analysis/modeling 66% 76% -10% Strategic insights consulting 63% 57% +6% Research outsourcing 61% 41% +20% CX/UX/VoC 53% 57% -4% Other 3% 1% +2% Average number of roles: 3.9 3.7 +0.2 n = 175 152 Takeaway: Insights operations is the most widely recognized role across both brand-side segments (82% researchers, 83% analytics); researchers are much more likely to include research outsourcing as significant (61% to 41%), while analytics professionals are more likely to include data analysis/modeling (76% to 66%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ALL SIGNIFICANT INSIGHTS PROFESSIONAL ROLES: GRIT WAVE (BRAND: RESEARCH) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A – 25A Insights operations N/A N/A N/A N/A N/A 82% N/A In-house research 62% 70% 65% 70% 75% 68% -7% Strategic insights consulting 67% 67% 62% 58% 66% 63% -3% Data analysis/modeling 44% 70% 51% 75% 68% 66% -2% Research outsourcing 46% 45% 41% 56% 60% 61% +1% CX/UX/VoC 61% 71% 66% 64% 61% 53% -8% Average number of roles: 2.8 3.2 2.9 3.2 3.3 3.9 +0.6 n = 271 251 211 191 191 175 Takeaway: Among brand-side researchers, the number who say research outsourcing is a significant role for insights professionals has grown from 46% in 21A to 61% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ALL SIGNIFICANT INSIGHTS PROFESSIONAL ROLES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A – 25A Insights operations N/A N/A N/A 83% N/A Data analysis/modeling 79% 90% 95% 76% -19% CX/UX/VoC 40% 38% 51% 57% +6% Strategic insights consulting 46% 52% 62% 57% -5% In-house research 45% 54% 56% 56% -- Research outsourcing 27% 34% 39% 41% +2% Average number of roles: 2.4 2.7 3.0 2.9 -0.1 n = 183 194 177 152 Takeaway: Peaking at 95% in 25A, data analysis/modeling declined sharply as a significant role for insights professionals from the brand-side analytics point of view, to 76% in 26A, while CX/UX/VoC continued a steady increase from 40% to 57% over the same period. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PRIMARY ROLE OF INSIGHTS PROFESSIONALS: BRAND SEGMENT Research Analytics Research – analytics In-house research 32% 6% +26% Insights operations 25% 32% -7% Strategic insights consulting 24% 9% +15% Data analysis/modeling 8% 33% -25% Research outsourcing 6% -- +6% CX/UX/VoC 3% 20% -17% Other 2% -- +2% n = 175 152 Takeaway: For 32% of brand-side researchers, in-house research is a primary role versus only 6% of analytics; 33% of analytics professionals cite data analysis/modeling versus 8% of researchers. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PRIMARY ROLE OF INSIGHTS PROFESSIONALS: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A In-house research 24% 33% 21% 30% 35% 32% 32% -- Insights operations N/A N/A N/A N/A N/A N/A 25% N/A Strategic insights consulting 36% 36% 33% 32% 27% 42% 24% -18% Data analysis/modeling 3% 5% 14% 10% 15% 7% 8% +1% Research outsourcing 6% 10% 5% 6% 7% 3% 6% +3% CX/UX/VoC 28% 16% 25% 22% 17% 15% 3% -12% n = 173 152 251 211 191 202 175 Takeaway: Among brand-side researchers, strategic insights consulting as a primary role declined from 42% in 25A to 24% in 26A, while CX/UX/VoC dropped from 15% to 3% as insights operations (32%) was introduced. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PRIMARY ROLE OF INSIGHTS PROFESSIONALS: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Data analysis/modeling 48% 58% 60% 33% -27% Insights operations N/A N/A N/A 32% N/A CX/UX/VoC 18% 10% 10% 20% 10% Strategic insights consulting 14% 11% 21% 9% -12% In-house research 15% 17% 4% 6% +2% Research outsourcing 4% 4% 4% 0% -4% n = 183 194 177 152 Takeaway: Among brand-side analytics professionals, data analysis/modeling as a primary role fell sharply from 60% in 25A to 33% in 26A, coinciding with the first appearance of insights operations as a tracked category (32% in 26A). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ALL OTHER SIGNIFICANT INSIGHTS PROFESSIONAL ROLES: PRIMARY ROLE (BRAND: RESEARCH) Insights operations In-house research Strategic insights consulting Data analysis/modeling Research outsourcing CX/UX/VoC 48% 58% 50% 60% 42% Data analysis/modeling 68% 65% 61% 60% In-house research 53% 67% 36% 22% Insights operations 71% 96% 69% 62% Research outsourcing 59% 63% 67% 26% Strategic insights consulting 56% 57% 34% 48% Other 0% 0% 3% 0% 0% Average number of secondary roles: 2.8 3.1 3.4 2.3 2.3 n = 52 47 39 18 12 CX/UX/VoC and “other” not shown due to very low n. Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Among brand-side researchers, those whose primary role is strategic insights consulting report the broadest secondary role portfolio (average 3.4 roles), with 96% also citing insights operations as significant. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ALL OTHER SIGNIFICANT INSIGHTS PROFESSIONAL ROLES: PRIMARY ROLE (BRAND: ANALYTICS) Data analysis/modeling Insights operations CX/UX/VoC Strategic insights consulting CX/UX/VoC 60% 35% 33% Data analysis/modeling 62% 80% 50% In-house research 62% 38% 68% 43% Insights operations 79% 78% 78% Research outsourcing 36% 29% 72% 32% Strategic insights consulting 56% 53% 54% Other 0% 3% 0% 0% Average number of secondary roles: 2.9 2.2 3.5 2.4 n = 53 52 27 13 Research outsourcing, in-house research and “other” not shown due to very low (or no) n. Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Among brand-side analytics professionals, those primarily in CX/UX/VoC report the broadest secondary portfolio (average 3.5 roles), with 80% also citing data analysis/modeling and 78% citing insights operations as significant. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. NATURE OF THE WORK | BRAND POV [DATA] PERCENTAGE OF B2B PROJECTS VERSUS B2C: BRAND SEGMENT Research Analytics All of them were B2B; none were B2C 14% 16% Most of them were B2B, but not all 24% 39% At least 25% B2B, but not most 17% 28% Some were B2B, but fewer than 25% 22% 15% None of them are B2B; all were B2C 22% 3% n = 164 147 Takeaway: Brand-side analytics professionals are much more B2B-oriented than researchers: 55% report most or all projects are B2B, compared to 38% of researchers; 22% of researchers report exclusively B2C work versus only 3% of analytics. Source: GRIT 2026 Insights Practice Report, Greenbook ALLOCATION OF QUALITATIVE AND QUANTITATIVE PROJECTS: BRAND SEGMENT Research Analytics Quantitative only 45% 33% Qualitative only 24% 24% Both quantitative and qualitative 28% 39% Neither qualitative nor quantitative 4% 4% n = 170 148 Takeaway: More brand-side researchers report that all projects are quantitative (45% vs. 33%), while analytics professionals are more likely to report qualiquant projects (39% vs. 28%). Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPES WORK WITH AT LEAST OCCASIONALLY: BRAND SEGMENT Research Analytics Technology 92% 96% Full-service research 84% 81% Qualitative research 83% 91% Data & analytics 74% 91% Field services 72% 72% Strategic consultancies 67% 88% n = 176 152 Takeaway: Nearly all brand-side researchers (92%) and analytics professionals (96%) work with technology providers at least occasionally; analytics professionals are more likely to engage data and analytics firms (91% to 74%) and strategic consultancies (88% to 67%). Source: GRIT 2026 Insights Practice Report, Greenbook CORPORATE PROFILES | BRAND POV [DATA] NUMBER OF INSIGHTS PROFESSIONALS: BRAND SEGMENT 1 to 4 staff 5 to 9 staff 10 to 19 staff 20 to 99 staff 100 or more staff Research (n = 173) 29% 20% 19% 22% 10% Analytics (n = 150) 7% 17% 18% 31% 26% Takeaway: Among brand-side researchers, 49% say there are fewer than 10 insights professionals on staff where they work, while only 24% of analytics professionals say the same. Conversely, 57% of analytics professionals say the staff size is 20 or more compared to only 32% of researchers. Source: GRIT 2026 Insights Practice Report, Greenbook NUMBER OF INSIGHTS PROFESSIONALS: GRIT WAVE (BRAND: RESEARCH) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A 1 to 4 staff 38% 31% 43% 30% 30% 36% 29% -7% 5 to 9 staff 23% 27% 23% 29% 29% 20% 20% -- 10 to 19 staff 13% 13% 15% 15% 15% 17% 19% +2% 20 or more staff 25% 29% 20% 26% 26% 32% 32% -- n = 270 244 208 186 186 198 173 Takeaway: The distribution of team sizes among brand-side researchers has shifted upward since 23A, with small staffs (1–4 professionals) decreasing from 43% to 29% and larger staff (20+) increasing from 20% to 32%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. NUMBER OF INSIGHTS PROFESSIONALS: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A 1 to 4 staff 22% 11% 13% 7% -6% 5 to 9 staff 14% 17% 12% 17% +5% 10 to 19 staff 13% 16% 15% 18% +3% 20 or more staff 51% 56% 57% 57% -- n = 175 190 175 150 Takeaway: Since 23A most brand-side analytics professionals report 20 or more insights professionals on staff (currently 57%) while those with small staffs (1–4 professionals) has fallen from 22% to 7%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PROFESSIONALS IN FORMAL INSIGHTS GROUP: BRAND SEGMENT Yes, all of them Yes, some of them None of them Research (n = 158) 52% 39% 9% Analytics (n = 147) 14% 80% 6% Takeaway: Brand-side researchers are far more likely to say that all insights professionals on staff work within a formal insights group (52% versus 14%). Source: GRIT 2026 Insights Practice Report, Greenbook PROFESSIONALS IN FORMAL INSIGHTS GROUP: GRIT WAVE (BRAND: RESEARCH) 23A 24A 25A 26A 26A - 25A Yes, all of them 61% 65% 65% 52% -13% Yes, some of them 29% 28% 30% 39% +9% None of them 10% 7% 5% 9% +4% n = 188 171 178 158 Takeaway: The share of brand-side researchers stating that all insights staff work in a formal group dropped from 65% in 25A to 52% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. PROFESSIONALS IN FORMAL INSIGHTS GROUP: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Yes, all of them 22% 25% 27% 14% -13% Yes, some of them 67% 67% 64% 80% +16% None of them 12% 9% 9% 6% -3% n = 162 167 163 147 Takeaway: The share of brand-side analytics professionals stating that all insights staff work in a formal group dropped from 27% in 25A to 14% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. COMPANY SIZE: BRAND SEGMENT Research Analytics 500 or fewer employees 25% 20% 501 to 4,999 employees 24% 23% 5,000 to 24,999 employees 26% 26% 25,000 to 49,999 10% 9% 50,000 or more 15% 23% n = 175 151 Takeaway: Company size distributions are similar across brand-side segments, though analytics professionals are somewhat more likely to be at very large companies (50,000 or more employees: 23% versus. 15%). Source: GRIT 2026 Insights Practice Report, Greenbook SIGNIFICANT MARKETS - LARGEST GAPS: BRAND SEGMENT Research Analytics Research - analytics Consumer packaged goods (CPG/FMCG) 25% 16% +9% Public sector, education, or NFP 14% 6% +8% Consumer durables & home products 8% 13% -5% Technology & telecom 28% 35% -7% Financial services 26% 38% -12% n = 162 141 Takeaway: Financial services shows the largest market gap between brand-side segments (38% analytics versus 26% researchers), while CPG/FMCG skews toward researchers (25% vs. 16%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. SIGNIFICANT MARKETS - OTHER GAPS: BRAND SEGMENT Research Analytics Research - analytics Media, entertainment, & sports 12% 11% +1% Transport, logistics, & shipping 7% 6% +1% Retail & ecommerce 16% 17% -1% Hospitality, travel, & leisure 9% 10% -1% Healthcare & pharmaceuticals 16% 17% -1% Industrial & manufacturing 11% 13% -2% Professional & business services 10% 12% -2% Automotive 11% 13% -2% Market research, insights, or analytics 8% 12% -4% n = 162 141 Takeaway: Market representation is similar across brand-side researchers and analytics professionals for industries outside of financial services, CPG, technology and telecom, consumer durables, and public sector and NFP. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. THE BIG PICTURE [STRATEGIC Interpretation] GRIT’s two brand-side segments — research and analytics — are archetypes defined by organizational placement rather than skill, and their cores are pulling apart even as they share a broad middle. Analytics professionals are increasingly concentrated in analytics/Data Science departments (27% → 52% since 23A) and researchers in insights/research groups (53% → 67% since 22A). At the same time, both segments report the same −13% drop this wave in insights professionals belonging to a formal group, even as insights staff sizes are generally growing — a pattern pointing to the insights function expanding into the organization through embedded, distributed specialists rather than contracting. The debut of “insights operations” as a significant role at 80%+ in both segments fits this: as more insights work is done by non-specialists, a coordinating layer emerges. Consistent with a broader mainstreaming of analytics, data analysis and modeling fell as a primary role among analytics professionals from 60% to 33% (25A → 26A). GRIT reads these signals as a possible move toward a hub-and-spoke model, in which insights professionals increasingly manage insights capacity that does not report to them. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Scope of Insights Impact This section examines how brand-side researchers and analytics professionals spend time with respect to business topics, and which business disciplines the insights functions leads or makes contributions. ARE RESEARCH AND ANALYTICS SEPARATE DOMAINS? | BRAND POV [ORIENTATION] TOP FIVE AREAS INSIGHTS PROFESSIONALS LEAD OR CONTRIBUTE: BRAND SEGMENT Research Analytics Research - analytics Consumer market insights 90% 86% +4% Competitive & market intelligence 90% 94% -4% Product development & innovation 89% 87% +2% Business intelligence & reporting 85% 96% -11% Advertising & communications research 82% 79% +3% Customer experience (CX) 79% 89% -10% Data Science & advanced analytics 68% 90% -22% n = 175 152 Green shading indicates top five areas led by segment. Takeaway: The top areas which insights professionals lead or contribute to are similar across both brand-side segments; the biggest difference is Data Science and advanced analytics (68% for researchers to 90% for analytics). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. TOP FIVE AREAS LED BY INSIGHTS PROFESSIONALS: BRAND SEGMENT Research Analytics Research - analytics Consumer market insights 62% 36% +26% Competitive & market intelligence 40% 38% +2% Advertising & communications research 37% 21% +16% Business intelligence & reporting 29% 51% -22% Shopper insights 29% 27% +2% Product development & innovation 27% 31% -4% Data Science & advanced analytics 24% 58% -34% n = 175 152 Green shading indicates top five areas led by segment. Takeaway: Brand-side researchers are much more likely to lead consumer market insights (62% versus 36% for analytics), while Data Science and advanced analytics is twice as likely to be led by analytics professionals (58% vs. 24%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. HOW INSIGHTS PROFESSIONALS SPEND THEIR TIME| BRAND POV [DATA] ON WHICH DO YOU SPEND A SIGNIFICANT AMOUNT OF YOUR TIME? (BRAND) WHICH AREAS ARE DIRECTLY IMPACTED BY YOUR INSIGHTS PROFESSIONALS? (BRAND) 26A Wording 25A Wording Advertising, media, & campaign performance Advertising or media Brand strategy & positioning Brand positioning Brand tracking Brand tracking Customer satisfaction, loyalty, & value Customer satisfaction or loyalty Digital, online, & website experience Consumer/shopper experience (online or digital) Website experience optimization Market structure, competition, & opportunity Customer share of wallet or lifetime value Partner/channel selection or optimization Partner/channel selection or optimization Pricing Pricing Product or service development - early stage Product or service development - early stage Product or service development - later stage Product or service development - later stage Segmentation & audience definition Segmentation Shopper behavior & offline experience Consumer/shopper experience (offline) [not included] Consumer shopping/purchase behavior [not included] Attitudes and opinions [not included] Competitive assessment [not included] Market size or opportunity [not included] Marketing mix Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. TOP BUSINESS TOPICS ON WHICH SPEND SIGNIFICANT TIME (BRAND: RESEARCH) Segmentation & audience definition 62% Brand strategy & positioning 59% Product/service development - early stage 58% n = 175 Takeaway: Most brand-side researchers spend significant time on segmentation and audience definition (62%), brand strategy and positioning (59%), and early-stage product/service development (58%). Source: GRIT 2026 Insights Practice Report, Greenbook TOP BUSINESS TOPICS ON WHICH SPEND SIGNIFICANT TIME (BRAND: ANALYTICS) Market structure, competition, & opportunity 48% Customer satisfaction, loyalty, & value 46% Product/service development - later stage 42% Segmentation & audience definition 42% Digital, online, & website experience 41% Product/service development - early stage 41% n = 152 Takeaway: Brand-side analytics professionals are most likely to spend significant time on market structure, competition, and opportunity (48%) and customer satisfaction, loyalty, and value (46%), but no single area dominates. Source: GRIT 2026 Insights Practice Report, Greenbook WHERE GRIT PARTICIPANTS SPEND SIGNIFICANT TIME: BRAND SEGMENT Research Analytics Research - analytics Segmentation & audience definition 62% 42% +20% Brand strategy & positioning 59% 36% +23% Product/service development - early stage 58% 41% +17% Brand tracking 49% 17% +32% Market structure, competition, & opportunity 47% 48% -1% Product or service development - later stage 47% 42% +5% Customer satisfaction, loyalty, & value 47% 46% +1% Advertising, media, & campaign performance 34% 32% +2% Shopper behavior & offline experience 33% 14% +19% Digital, online, & website experience 28% 41% -13% Pricing 22% 38% -16% Partner/channel selection or optimization 16% 37% -21% None of these 1% 1% -- Average number of significant areas: 5.0 4.3 +0.7 n = 175 152 Takeaway: Brand tracking shows the largest gap between brand-side segments (49% of researchers vs. 17% of analytics), followed by brand strategy and positioning (59% to 36%) and segmentation and audience definition (62% to 42%). Analytics professionals are more likely to lead partner/channel selection (37% to 16%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. GRIT PARTICIPANTS’ PRIMARY FOCUS: BRAND SEGMENT Research Analytics Research - analytics Brand strategy & positioning 19% 5% +14% Product or service development - early stage 17% 14% +3% Customer satisfaction, loyalty, & value 17% 12% +5% Market structure, competition, & opportunity 12% 18% -6% Segmentation & audience definition 8% 7% -1% Advertising, media, & campaign performance 7% 9% -2% Brand tracking 6% 2% +4% Product or service development - later stage 5% 9% -4% Shopper behavior & offline experience 4% 1% +3% Digital, online, & website experience 4% 8% -4% Pricing 1% 6% -5% Partner/channel selection or optimization -- 9% -9% n = 166 139 Takeaway: Brand strategy and positioning is the top primary focus for brand-side researchers (19%), while analytics professionals are most likely to cite market structure, competition & opportunity (18%) or early-stage product development (14%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. WHAT INSIGHTS PROFESSIONALS LEAD | BRAND POV [DATA] DISCIPLINES INSIGHTS PROFESSIONALS LEAD: BRAND SEGMENT Research Analytics Research - analytics Consumer market insights 62% 36% +26% Competitive & market intelligence 40% 38% +2% Advertising & communications research 37% 21% +16% Business intelligence & reporting 29% 51% -22% Shopper insights 29% 27% +2% Product development & innovation 27% 31% -4% Customer experience (CX) 27% 26% +1% Data Science & advanced analytics 24% 58% -34% Brand management 15% 17% -2% Digital UX & web analytics 14% 20% -6% Average number of disciplines lead: 3.1 3.2 -0.1 n = 175 152 Takeaway: The largest brand-side leadership gaps are in Data Science and advanced analytics (58% analytics versus 24% researchers) and consumer market insights (36% analytics to 62% researchers). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. From the researcher perspective, consumer market insights (62%), competitive and market intelligence (40%), advertising and communications research (37%), and shopper insights are perennially among the top five disciplines led by insights professionals. Consumer market insights, however, fell from 74% to 62% while remaining the most frequently named. DISCIPLINES LED BY INSIGHTS PROFESSIONALS: GRIT WAVE (BRAND: RESEARCH) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Consumer market insights 70% 73% 73% 70% 74% 62% -12% Competitive & market intelligence 24% 29% 36% 32% 33% 40% +7% Advertising & communications research 41% 44% 48% 37% 42% 37% -5% Business intelligence & reporting 21% 25% 28% 26% 24% 29% +5% Shopper insights 35% 37% 37% 31% 31% 29% -2% Customer experience (CX) 31% 36% 35% 34% 40% 27% -13% Product development & innovation 15% 11% 20% 21% 16% 27% +11% Data Science & advanced analytics N/A N/A N/A N/A N/A 24% N/A Data Science 16% 15% 18% 23% 16% N/A N/A Big Data analytics 13% 18% 15% 21% 13% N/A N/A Brand management 13% 12% 19% 11% 19% 15% -4% Digital UX & web analytics N/A N/A N/A N/A N/A 14% N/A Usability 13% 16% 20% 21% 16% N/A N/A Web analytics 13% 9% 14% 12% 10% N/A N/A Average number of disciplines led: 3.1 3.3 3.6 3.4 3.3 3.1 -0.2 n = 271 251 211 190 202 175 Green shading indicates top five within wave. Takeaway: Among brand-side researchers, their top five areas led have always included consumer market insights (62%), competitive and market intelligence (40%), advertising and communications research (37%), and shopper insights (29%). In 26A, business intelligence and reporting (29%) edged CX out of the top five. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. DISCIPLINES LED BY INSIGHTS PROFESSIONALS: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Data Science & advanced analytics N/A N/A N/A 58% N/A Data Science 33% 48% 60% N/A N/A Big Data analytics 40% 52% 59% N/A N/A Business intelligence & reporting 42% 51% 61% 51% -10% Competitive & market intelligence 33% 40% 41% 38% -3% Consumer market insights 38% 41% 48% 36% -12% Product development & innovation 30% 22% 29% 31% +2% Shopper insights 27% 19% 17% 27% +10% Customer experience (CX) 40% 27% 35% 26% -9% Advertising & communications research 36% 18% 22% 21% -1% Digital UX & web analytics N/A N/A N/A 20% N/A Usability 26% 23% 24% N/A N/A Web analytics 35% 31% 34% N/A N/A Brand management 28% 13% 15% 17% +2% Average number of disciplines led: 4.1 3.8 4.5 3.2 -1.3 n = 183 194 177 152 Green shading indicates top five within wave. Takeaway: Among brand-side analytics professionals, their top five areas led have always included Data Science and advanced analytics (58%), business intelligence and reporting (51%), and consumer market insights (36%). Product development and innovation (31%) entered the top five in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. WHERE INSIGHTS PROFESSIONALS CONTRIBUTE | BRAND POV [DATA] DISCIPLINES INSIGHTS PROFESSIONALS LEAD OR CONTRIBUTE: BRAND SEGMENT Research Analytics Research - analytics Consumer market insights 90% 86% +4% Competitive & market intelligence 90% 94% -4% Product development & innovation 89% 87% +2% Business intelligence & reporting 85% 96% -11% Advertising & communications research 82% 79% +3% Customer experience (CX) 79% 89% -10% Brand management 79% 72% +7% Data Science & advanced analytics 68% 90% -22% Shopper insights 63% 72% -9% Digital UX & web analytics 55% 80% -25% Average number of disciplines lead or contribute: 7.8 8.5 -0.7 n = 175 152 Takeaway: Brand-side analytics professionals are more likely than researchers to lead or contribute to digital UX & web analytics (80% to 55%) and Data Science and advanced analytics (90% to 68%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. DISCIPLINES INSIGHTS PROFESSIONALS LEAD OR CONTRIBUTE: GRIT WAVE (BRAND: RESEARCH) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Competitive & market intelligence 88% 86% 88% 87% 87% 90% +3% Consumer market insights 92% 98% 93% 92% 96% 90% -6% Product development & innovation 87% 89% 86% 89% 89% 89% -- Business intelligence & reporting 84% 85% 84% 84% 86% 85% -1% Advertising & communications research 74% 85% 80% 76% 80% 82% +2% Customer experience (CX) 87% 92% 90% 91% 91% 79% -12% Brand management 86% 85% 89% 80% 87% 79% -8% Data Science & advanced analytics N/A N/A N/A N/A N/A 68% N/A Data Science 67% 64% 64% 72% 71% N/A N/A Big Data analytics 64% 63% 62% 62% 65% N/A N/A Shopper insights 62% 64% 69% 59% 64% 63% -1% Digital UX & web analytics N/A N/A N/A N/A N/A 55% N/A Usability 73% 74% 75% 76% 74% N/A N/A Web analytics 51% 49% 52% 54% 50% N/A N/A Average number of disciplines led or contribute: 9.2 9.3 9.3 9.2 9.4 7.8 -1.6 n = 271 251 211 190 202 175 Green shading indicates top five within wave. Takeaway: Among the areas brand-side researchers lead or contribute, competitive & market intelligence (90%), consumer market insights (90%), and product development and innovation (89%) have always been among the top five. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. DISCIPLINES INSIGHTS PROFESSIONALS LEAD OR CONTRIBUTE: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Business intelligence & reporting 91% 94% 93% 96% +3% Competitive & market intelligence 85% 90% 93% 94% +1% Data Science & advanced analytics N/A N/A N/A 90% N/A Data Science 82% 89% 97% N/A N/A Big Data analytics 87% 92% 94% N/A N/A Customer experience (CX) 91% 85% 91% 89% -2% Product development & innovation 86% 85% 87% 87% -- Consumer market insights 85% 87% 89% 86% -3% Digital UX & web analytics N/A N/A N/A 80% N/A Web analytics 84% 77% 91% N/A N/A Usability 87% 81% 85% N/A N/A Advertising & communications research 68% 69% 66% 79% +13% Shopper insights 63% 56% 62% 72% +10% Brand management 74% 71% 73% 72% -1% Average number of disciplines led or contribute: 9.8 9.8 10.2 8.5 -1.7 n = 183 194 177 152 Green shading indicates top five within wave. Takeaway: Among the areas brand-side analytics lead or contribute, business intelligence and reporting (96%), competitive and market intelligence (94%), and Data Science and advanced analytics (90%) have always been in the top five. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. THE BIG PICTURE [STRATEGIC Interpretation] Brand-side researchers and analytics professionals contribute to many of the same disciplines but lead in different ones: researchers are far likelier to say insights leads consumer market insights, analytics to say it leads Data Science, advanced analytics, and business intelligence/reporting. These domains are well delineated but not siloed. On average, researchers say insights professionals contribute to about 78% of the ten disciplines GRIT tracks and analytics professionals 85% — little changed from last year. More telling is a decline in domain leadership even where contribution holds steady: among researchers, leading consumer market insights fell to 62% (−12%); among analytics, leading business intelligence/reporting fell −10%. This may indicate that such work is increasingly performed by end users and non-specialists rather than owned by insights teams. How participants spend their time reinforces the contrast: researchers are more homogeneous, spending significant time across an average of 5.0 topics, while analytics professionals are more specialized at 4.3 topics with none reaching a majority — consistent with analytics becoming less a standalone specialty than a skill embedded in specific business functions. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Evolving Supplier Landscape From the perspectives of tech-led suppliers and service-led suppliers across employee size bands, this section discusses how the supplier landscape has evolved with respect to revenue sources and service offering portfolios. HOW IS THE SUPPLIER LANDSCAPE CHANGING? [ORIENTATION] SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE BY SUPPLIER HIGHEST REVENUE SOURCE Full-service Field services Qualitative research Strategic consulting Technology Data & analytics Other 21A (n = 769) 52% 5% 19% 9% 13% 2% 22A (n = 1,002) 48% 9% 14% 17% 13% 0% 23A (n = 731) 45% 9% 9% 15% 11% 8% 3% 24A (n = 627) 41% 12% 12% 15% 10% 10% 0% 25A (n = 595) 53% 8% 7% 13% 9% 8% 2% 26A (n = 387) 51% 8% 9% 14% 10% 8% 0% Qualitative research was not broken out prior to 23B. Takeaway: Full-service research has been the dominant revenue source throughout the tracked period, ranging from 41% to 53% across waves, with no other category exceeding 19% in any wave. Source: GRIT 2026 Insights Practice Report, Greenbook PROPORTION OF ALL SERVICES OFFERED: SUPPLIER SEGMENT Research Consulting Technology Offline field services Tech-led (n = 39) 23% 25% 37% 15% Service-led: ≤20 FTE (n = 158) 29% 33% 15% 22% Service-led: 21-100 FTE (n = 79) 29% 30% 21% 20% Service-led: 101-500 FTE (n = 56) 29% 26% 21% 23% Service-led: 500+ FTE (n = 55) 29% 28% 24% 19% Darker green indicates higher average number; yellowish, middle average number; and darker red, lower average number. Takeaway: Tech-led suppliers allocate a notably higher share of their offerings to technology (37%) compared to all service-led segments (15% to 24%), while service-led segments each allocate 29% to research services. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER COMPOSITION BY REVENUE SOURCE | SUPPLIER POV [DATA] SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE (SUPPLIER) Full or field service Technology Data and analytics Strategic consulting Other 20A (n = 789) 42% 12% 14% 30% 2% 21A (n = 766) 57% 9% 13% 19% 2% 22A (n = 1,002) 58% 16% 12% 13% 1% 23A (n = 731) 55% 11% 8% 14% 11% 24A (n = 628) 53% 10% 10% 15% 12% 25A (n = 598) 62% 9% 8% 12% 9% 26A (n = 387) 58% 10% 8% 14% 9% *Full-service research and field services combined through 20B. Qualitative research was not broken out prior to 23B. Takeaway: Full-service and field service combined has ranged from 53% to 62% across waves since the start of the pandemic, and technology, data & analytics, and strategic consulting each have accounted for 19% or less. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE (SUPPLIER) Full-service research 51% Strategic consulting 14% Technology 10% Field services 8% Data and analytics 8% Qualitative research 9% Other 0% n = 387 Takeaway: Full-service research accounts for just over half (51%) of supplier-side professionals by primary revenue source; all other categories are 14% or below. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE (SUPPLIER) Full-service research (≤20 FTE) 18% Full-service research (21 to 500 FTE) 24% Full-service research (500+ FTE) 9% Field Services 8% Qualitative research 9% Strategic consultancy (≤20 FTE) 7% Strategic consultancy (21 to 500 FTE) 4% Strategic consultancy (500+ FTE) 3% Technology (≤100 FTE) 7% Technology (100+ FTE) 4% Data and analytics (≤100 FTE) 4% Data and analytics (100+ FTE) 4% Other 0% n = 387 Takeaway: Mid-size full-service research firms (21 to 500 FTE) represent the largest single slice of the supplier landscape at 24%, while all technology and data & analytics segments combined account for 19%. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE (SUPPLIER) 21A 22A 23A 24A 25A 26A 26A - 25A Full-service research (≤20 FTE) 19% 11% 11% 16% 19% 18% -1% Full-service research (21 to 500 FTE) 24% 30% 28% 19% 24% 24% -- Full-service research (500+ FTE) 9% 7% 6% 6% 10% 9% -1% Field Services 5% 9% 9% 12% 8% 8% -- Qualitative research 9% 12% 7% 9% +2% Strategic consultancy (≤20 FTE) 11% 7% 7% 5% 7% 7% -- Strategic consultancy (21 to 500 FTE) 6% 3% 3% 7% 4% 4% -- Strategic consultancy (500+ FTE) 3% 4% 5% 3% 2% 3% 1% Technology (<=100 FTE) 5% 7% 6% 5% 5% 7% +2% Technology (100+ FTE) 4% 10% 5% 5% 4% 4% -- Data and analytics (<=100 FTE) 8% 7% 4% 5% 5% 4% -1% Data and analytics (100+ FTE) 5% 6% 4% 5% 3% 4% +1% Other 2% 0% 3% 0% 2% 0% -2% n = 769 1,002 731 627 595 387 Qualitative research not introduced until 23B. Takeaway: The composition of the supplier landscape has been relatively stable across waves; smaller data and analytics and strategic consultancies may be contracting. Source: GRIT 2026 Insights Practice Report, Greenbook. SUPPLIER SEGMENT EVOLUTION | SUPPLIER POV [DATA] SUPPLIER SEGMENT SIZES Tech-led 10% Service-led: <20 FTE 35% Service-led: 21-100 FTE 21% Service-led: 101-500 FTE 15% Service-led: 500+ FTE 18% n = 387 Takeaway: Service-led suppliers make up 90% of GRIT supplier-side professionals; the largest single segment is service-led ≤20 FTE (35%). Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE: SERVICE-LED SEGMENT Full-service Field services Qualitative research Strategic consulting Data & analytics Service-led: ≤20 FTE (n = 158) 51% 5% 17% 20% 7% Service-led: 21-100 FTE (n = 79) 61% 11% 9% 11% 9% Service-led: 101-500 FTE (n = 56) 71% 11% 3% 10% 5% Service-led: 500+ FTE (n = 55) 49% 10% 3% 20% 17% Takeaway: Full-service research is the primary revenue source for nearly half or more of service-led suppliers across all size bands, ranging from 49% (500+ FTE) to 71% (101–500 FTE); strategic consulting skews toward the smallest (20%) and largest (20%) service-led firms. Source: GRIT 2026 Insights Practice Report, Greenbook GRIT SEGMENT: GRIT WAVE BY SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE 21A (n = 766) 9% 38% 22% 15% 16% 22A (n = 1,002) 16% 31% 19% 17% 16% 23A (n = 724) 11% 34% 24% 15% 15% 24A (n = 628) 10% 32% 25% 16% 16% 25A (n = 595) 9% 36% 23% 15% 17% 26A (n = 387) 10% 35% 21% 15% 18% Takeaway: The relative size of each supplier segment has been consistent across waves since 21A, with service-led ≤20 FTE holding the largest share (31–38%) and tech-led consistently the smallest (9–16%) throughout. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE (SERVICE-LED: 500+ FTE) Full-service Field services Qualitative research Strategic consulting Data & analytics Other 21A (n = 119) 59% 2% 19% 20% 0% 22A (n = 160) 58% 8% 14% 20% 0% 23A (n = 97) 54% 8% 1% 25% 10% 3% 24A (n = 104) 40% 12% 16% 18% 13% 0% 25A (n = 98) 63% 9% 3% 14% 9% 1% 26A (n = 55) 49% 10% 3% 20% 17% 0% Qualitative research not introduced until 23B. Takeaway: Full-service research has been the dominant revenue source for 500+ FTE service-led suppliers throughout the tracked period (49% to 63%), followed by strategic consulting (20% currently) and data and analytics (17% currently). Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE (SERVICE-LED: 101-500 FTE) Full-service Field services Qualitative research Strategic consulting Data & analytics Other 21A (n = 116) 69% 3% 10% 16% 2% 22A (n = 174) 61% 17% 7% 14% 0% 23A (n = 102) 64% 7% 4% 5% 16% 4% 24A (n = 110) 45% 16% 4% 16% 18% 1% 25A (n = 87) 67% 12% 1% 10% 9% 2% 26A (n = 56) 71% 11% 3% 10% 5% 0% Qualitative research not introduced until 23B. Takeaway: Full-service research has been the dominant revenue source for 101 to 500 FTE service-led suppliers and has grown from 45% in 24A to 71% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE (SERVICE-LED: 21-100 FTE) Full-service Field services Qualitative research Strategic consulting Data & analytics Other 21A (n = 172) 60% 6% 18% 15% 2% 22A (n = 195) 64% 12% 13% 11% 1% 23A (n = 184) 50% 17% 12% 13% 5% 3% 24A (n = 156) 46% 18% 11% 15% 9% 0% 25A (n = 133) 62% 12% 6% 10% 7% 3% 26A (n = 79) 61% 11% 9% 11% 9% 0% Qualitative research not introduced until 23B. Takeaway: Full-service research has been the dominant revenue source for 21 to 100 FTE service-led suppliers and has grown from 46% in 24A to 61% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook SUPPLIER TYPE/HIGHEST REVENUE: GRIT WAVE (SERVICE-LED: ≤20 FTE) Full-service Field services Qualitative research Strategic consulting Data & analytics Other 21A (n = 290) 51% 7% 28% 12% 2% 22A (n = 310) 51% 9% 23% 15% 2% 23A (n = 271) 46% 9% 15% 19% 9% 2% 24A (n = 197) 50% 8% 18% 15% 9% 0% 25A (n = 224) 52% 7% 13% 17% 9% 1% 26A (n = 158) 51% 5% 17% 20% 7% 0% Qualitative research not introduced until 23B. Takeaway: Except for 23A, half or more of service-led suppliers with ≤20 FTE suppliers claim full-service research as their primary revenue source, currently 51% and followed by strategic consulting (20%) and qualitative research (17%). Source: GRIT 2026 Insights Practice Report, Greenbook ALL SIGNIFICANT REVENUE SOURCES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Full-service research 31% 65% 90% 84% 69% Data and analytics 38% 25% 43% 48% 48% Strategic consulting 17% 47% 38% 47% 43% Qualitative research 10% 41% 38% 39% 31% Technology 100% 9% 23% 31% 23% Field services 19% 17% 30% 33% 16% Average number of sources 2.1 2.0 2.6 2.8 2.3 n = 39 158 79 56 55 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Data and analytics is the most frequent non-technology revenue source that is significant for tech-led suppliers (38%); for most service-led suppliers, full-service research is significant. Source: GRIT 2026 Insights Practice Report, Greenbook. ALL SIGNIFICANT REVENUE SOURCES: GRIT WAVE (TECH-LED) Full-service Field services Qualitative research Strategic consulting Data & analytics Other 21A (n = 69) 23% 7% 10% 29% 1% 22A (n = 163) 35% 18% 25% 39% 0% 23A (n = 70) 26% 9% 17% 9% 28% 0% 24A (n = 61) 37% 22% 25% 33% 33% 4% 25A (n = 53) 29% 18% 20% 14% 42% 0% 26A (n = 39) 31% 19% 10% 17% 38% 0% Qualitative research not introduced until 23B. Takeaway: Data and analytics is the most common non-technology revenue source for tech-led suppliers (38%), followed by full-service research (31%). Source: GRIT 2026 Insights Practice Report, Greenbook ALL SIGNIFICANT REVENUE SOURCES: GRIT WAVE (SERVICE-LED: 500+ FTE) Full-service Field services Qualitative research Strategic consulting Technology Data & analytics Other 21A (n = 119) 70% 15% 48% 10% 42% 0% 22A (n = 160) 80% 24% 46% 26% 51% 0% 23A (n = 97) 72% 23% 30% 54% 24% 38% 3% 24A (n = 104) 64% 30% 43% 44% 21% 43% 2% 25A (n = 97) 77% 30% 36% 46% 27% 43% 0% 26A (n = 55) 69% 16% 31% 43% 23% 48% 0% Qualitative research not introduced until 23B. Takeaway: Most service-led suppliers with 500+ FTE draw revenue from full-service research (69%), but that’s down -8% from 25A; field services also declined from 30% in 25A to 16% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook ALL SIGNIFICANT REVENUE SOURCES: GRIT WAVE (SERVICE-LED: 101-500 FTE) Full-service Field services Qualitative research Strategic consulting Technology Data & analytics Other 21A (n = 116) 80% 13% 45% 14% 34% 2% 22A (n = 174) 78% 28% 39% 26% 45% -- 23A (n = 102) 73% 17% 33% 28% 15% 43% 4% 24A (n = 110) 62% 26% 29% 36% 20% 48% 1% 25A (n = 87) 83% 23% 34% 32% 17% 41% -- 26A (n = 56) 84% 33% 39% 47% 31% 48% -- Qualitative research not introduced until 23B. Takeaway: Full-service research dominates as a significant revenue source among service-led suppliers with 101 to 500 FTE, and three other sources increased by double-digits since 25A: strategic consulting (32% to 47%), technology (17% to 31%), and field services (23% to 33%). Source: GRIT 2026 Insights Practice Report, Greenbook ALL SIGNIFICANT REVENUE SOURCES: GRIT WAVE (SERVICE-LED: 21-100 FTE) Full-service Field services Qualitative research Strategic consulting Technology Data & analytics Other 21A (n = 172) 70% 15% 41% 12% 32% 1% 22A (n = 195) 79% 23% 36% 15% 35% 1% 23A (n = 183) 67% 36% 33% 28% 16% 25% 1% 24A (n = 156) 71% 39% 48% 40% 19% 46% -- 25A (n = 133) 76% 25% 38% 38% 20% 37% -- 26A (n = 79) 90% 30% 38% 38% 23% 43% -- Qualitative research not introduced until 23B. Takeaway: As a significant revenue source, full-service research jumped from 76% of service-led suppliers with 21–100 FTE in 25A to 90% in 26A, its third straight increase. Source: GRIT 2026 Insights Practice Report, Greenbook ALL SIGNIFICANT REVENUE SOURCES: GRIT WAVE (SERVICE-LED: ≤20 FTE) Full-service Field services Qualitative research Strategic consulting Technology Data & analytics Other 21A (n = 290) 60% 13% 50% 4% 23% 3% 22A (n = 310) 68% 17% 50% 7% 31% 2% 23A (n = 271) 59% 16% 39% 45% 5% 25% 2% 24A (n = 197) 63% 18% 40% 39% 8% 28% 1% 25A (n = 224) 68% 17% 43% 41% 7% 31% 0% 26A (n = 158) 65% 17% 41% 47% 9% 25% 1% Qualitative research not introduced until 23B. Takeaway: Most service-led suppliers with ≤20 FTE claim full-service research as a significant revenue source (65%), followed by strategic consulting (47%) and qualitative research (41%). Source: GRIT 2026 Insights Practice Report, Greenbook SERVICE POSITIONING BY OFFERING | SUPPLIER POV [DATA] SERVICE MOST IMPORTANT TO POSITIONING: SUPPLIER SEGMENT (AT LEAST 5% OF ANY TWO SEGMENTS) Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Full-service research 7% 34% 42% 41% 33% More than one are equally most important 10% 15% 9% 21% 13% Strategic insights consulting -- 14% 13% 5% 10% Tech for basic or advanced analytics 12% 1% 1% -- 6% Tech for online quant data collection 19% 1% 2% -- 5% Sampling 2% 2% 7% 7% 4% n = 39 158 79 56 55 Takeaway: Full-service research is the leading offering most important for positioning among service-led suppliers, from 33% of those with 500+ FTE to 42% of those with 21 to 100 FTE; for tech-led suppliers, it’s technology for online quantitative data collection (19%). Source: GRIT 2026 Insights Practice Report, Greenbook. TECHNOLOGY OFFERING MOST IMPORTANT TO POSITIONING: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online quant data collection 19% 1% 2% -- 5% DIY surveys 12% -- -- 2% -- Basic or advanced analytics 12% 1% 1% -- 6% Online communities (MROC) 8% 1% 4% 2% 3% Collection and/or analysis of unstructured data 5% 2% -- -- -- DIY sample access 3% 1% -- -- 1% Synthetic data or synthetic sample 2% -- -- 1% -- Online qual data collection -- 2% 3% -- -- Passive data collection and/or analysis -- 1% -- -- -- Nonconscious data collection and/or analysis -- 1% 1% -- -- n = 39 158 79 56 55 Takeaway: Three technology offerings are named by at least 10% of the tech-led segment as most important to positioning: online quant data collection (19%), DIY surveys (12%), and basic or advanced analytics (12%). Source: GRIT 2026 Insights Practice Report, Greenbook. CONSULTING SERVICES MOST IMPORTANT TO POSITIONING: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Strategic insights consulting -- 14% 13% 5% 10% Technology consulting 8% 1% 1% -- 3% Marketing strategy consulting 2% 1% 2% -- 2% Brand management/strategy consulting -- 3% -- 4% 2% Customer or user experience (CX/UX) consulting 4% 1% 1% -- 1% Business strategy consulting 2% 1% 4% -- -- Product development/innovation consulting -- 1% 3% -- -- Marcom, advertising, or PR consulting -- 1% 1% 1% -- Other consulting services -- -- -- 4% -- n = 39 158 79 56 55 Takeaway: Strategic insights consulting is cited by as the offering most important to positioning by at least 10% of service-led segments: those with ≤20 FTE (14%), with 21-100 FTE (13%), and with 500+ FTE (10%). Source: GRIT 2026 Insights Practice Report, Greenbook. OFFLINE FIELD SERVICE MOST IMPORTANT TO POSITIONING: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Sampling 2% 2% 7% 7% 4% Offline qual data collection -- -- -- -- 3% Recruiting/pre-recruiting -- 2% -- 3% 1% Moderating/interviewing 2% 2% 2% 2% -- Offline quant data collection -- 2% -- 1% -- Interviewing facilities/locations -- -- -- -- -- n = 39 158 79 56 55 Takeaway: Offline field service offerings are infrequently cited by any segment as most important to positioning, with sampling reaching only 7% in the service-led supplier with 21-100 and 101-500 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook. RESEARCH SERVICE MOST IMPORTANT TO POSITIONING: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Full-service research 7% 34% 42% 41% 33% Syndicated data and/or reports -- 1% -- 1% 8% Analytical services 3% 4% 2% 3% 3% Secondary research -- 1% -- -- 2% Industry-focused research -- 5% 1% 2% -- Research/analysis based on unstructured data 2% 3% 1% -- -- Data services -- -- -- -- -- Applied neuroscience/biometrics research -- -- -- -- -- Other research services -- -- 1% -- -- n = 39 158 79 56 55 Takeaway: Full-service research is the offering most important to positioning for more than 30% of each service-led supplier segment and the leading research service among tech-led suppliers (7%); syndicated data and reports is most important for 8% of service-led with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook. OFFERINGS BY SERVICE CATEGORY | SUPPLIER POV [DATA] CONSULTING SERVICES OFFERINGS: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Strategic insights 45% 80% 79% 74% 75% Product development/innovation 36% 55% 58% 59% 67% Marketing strategy 32% 63% 52% 44% 60% Customer or user experience (CX/UX) 35% 48% 42% 46% 55% Brand management/strategy 22% 55% 61% 50% 51% Business strategy 24% 54% 50% 41% 50% Marketing communications, advertising, or PR 26% 47% 50% 51% 44% Technology consulting 48% 20% 25% 22% 29% Other consulting services 2% 3% 1% 6% 1% None of the above 17% 10% 8% 11% 7% Average number offered: 2.7 4.2 4.2 3.9 4.3 n = 39 158 79 56 55 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Strategic insights is the leading consulting offering in each segment, from 45% of tech-led suppliers to more than 70% of each service-led segment; product development and innovation and brand management/strategy are offered by at least half of each service-led segment. Source: GRIT 2026 Insights Practice Report, Greenbook. CONSULTING SERVICES OFFERED – CHANGE FROM 25A: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Strategic insights -2% +7% +6% +2% -11% Product development/innovation +4% +6% +8% +2% +3% Marketing strategy -2% +1% -2% -10% -3% Customer or user experience (CX/UX) -1% +1% -4% -2% -1% Brand management/strategy +1% -2% +7% -4% -15% Business strategy +1% -3% +5% -9% -12% Marketing communications, advertising, or PR +1% -1% +2% +2% -9% Technology consulting +11% +5% +3% +6% -6% Other consulting services +2% +3% +1% +6% +1% None of the above -18% -3% -8% -6% -2% Average number offered: +0.3 +0.3 0.3 -- -0.5 n = 39 158 79 56 55 Takeaway: Technology consulting increased +11% among tech-led suppliers from 25A to 26A, but the other big movers were downward: marketing strategy, -10% among service-led suppliers with 101-500 FTE, and brand management/strategy (-15%), business strategy (-12%), and strategic insights (-11%) among those with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook. RESEARCH SERVICES OFFERED: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Full-service research 46% 78% 85% 93% 83% Secondary research 17% 57% 48% 53% 64% Analytical services 53% 66% 77% 80% 61% Industry-focused research 32% 48% 48% 63% 60% Research/analysis based on unstructured data 38% 52% 57% 53% 59% Data services 54% 39% 58% 57% 54% Syndicated data and/or reports 21% 20% 25% 34% 51% Applied neuroscience/biometrics 2% 12% 18% 12% 25% Other research services 2% 1% -- -- -- None of the above 16% 3% 4% 4% 0% Average number offered: 2.6 3.7 4.2 4.5 4.6 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Majorities in each segment offer analytical services, from 53% of tech-led suppliers to 80% of service-led with 101-500 FTE; full-service research and research/analysis based on unstructured data also claim majorities of each service-led segment. Source: GRIT 2026 Insights Practice Report, Greenbook. RESEARCH SERVICES OFFERED – CHANGE FROM 25A: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Full-service research -4% -2% +2% +6% -5% Secondary research +7% +4% +5% +14% +3% Analytical services -11% +3% +11% +9% -16% Industry-focused research -3% -8% +5% +11% -8% Research/analysis based on unstructured data -5% +5% +13% -- -1% Data services +5% -1% +11% -7% -11% Syndicated data and/or reports +2% -- -6% +1% -4% Applied neuroscience/biometrics -2% +8% +9% +5% -3% Other research services -- -- -2% -2% -2% None of the above +2% -3% +1% +1% -5% Average number offered: -0.1 +0.1 +0.5 +0.4 -0.5 Takeaway: Three research services increased by double digits among service-led suppliers with 21-100 FTE: research and analysis based on unstructured data (+13%) and analytical and data services (+11% each); analytical services fell -16% and data services fell -11% among those with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook. OFFLINE FIELD SERVICES OFFERED: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Quantitative data collection (offline) 25% 55% 56% 55% 62% Moderating/interviewing 35% 62% 56% 72% 60% Qualitative data collection (offline) 24% 55% 51% 64% 57% Recruiting/pre-recruiting 29% 50% 52% 62% 47% Sampling 47% 38% 50% 58% 44% Interviewing facilities/locations 14% 28% 25% 41% 31% None of the above 33% 21% 16% 18% 19% Average number offered: 1.7 2.9 2.9 3.5 3.0 n = 39 158 79 56 55 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: In each service-led segment, majorities offer offline data collection services for quantitative data, moderating/interviewing, qualitative data collection, and recruiting/pre-recruiting. Source: GRIT 2026 Insights Practice Report, Greenbook. OFFLINE FIELD SERVICES OFFERED – CHANGE FROM 25A: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Quantitative data collection (offline) -19% +3% -3% +1% +4% Moderating/interviewing +10% -4% +3% +18% -7% Qualitative data collection (offline) -10% -1% +2% +8% -2% Recruiting/pre-recruiting -2% +6% +2% +11% -13% Sampling +3% +2% +1% +7% -9% Interviewing facilities/locations +3% -- -5% +14% +1% None of the above +10% -- -6% -3% -2% Average number offered: -0.4 -0.1 -0.2 +0.4 -0.5 Takeaway: Among service-led suppliers with 101-500 FTE, moderating/interviewing (+18%), interviewing facilities/locations (+14%), and recruiting/pre-recruiting (+11%) each increased by double digits, while moderating/interviewing increased +10% in the tech-led segment. Source: GRIT 2026 Insights Practice Report, Greenbook. TECHNOLOGY OFFERED: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Basic or advanced analytics 68% 38% 45% 52% 69% Collection and/or analysis of unstructured data 65% 32% 38% 40% 37% Online quantitative data collection 65% 39% 54% 58% 59% DIY surveys 55% 9% 24% 18% 37% Online qualitative data collection 48% 36% 47% 48% 41% DIY sample access 40% 4% 18% 16% 29% Online communities (MROC) 38% 17% 29% 38% 40% Synthetic data or synthetic sample 20% 8% 15% 24% 36% Passive data collection and/or analysis 12% 8% 8% 15% 19% Nonconscious data collection and/or analysis 8% 6% 16% 11% 13% None of the above 2% 43% 22% 25% 8% Average number offered: 4.2 2.0 2.9 3.2 3.8 n = 39 158 79 56 55 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Most tech-led suppliers offer technology for basic or advanced analytics (68%), collection and/or analysis of unstructured data (65%), online quantitative data collection (65%), and DIY surveys (55%); most service-led suppliers with 20+ FTE offer technology for online quantitative data collection. Source: GRIT 2026 Insights Practice Report, Greenbook. TECHNOLOGY OFFERED – CHANGE FROM 25A: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Basic or advanced analytics -8% +1% -12% -9% +2% Collection and/or analysis of unstructured data +5% +5% -7% -4% -13% Online quantitative data collection -2% -3% -14% -7% -7% DIY surveys +2% -4% +6% -19% -22% Online qualitative data collection -1% -- -2% -2% -19% DIY sample access +1% -3% -3% -4% -6% Online communities (MROC) +9% -3% -3% -- -9% Synthetic data or synthetic sample -1% +4% +5% +12% +5% Passive data collection and/or analysis +3% +2% -1% +1% -9% Nonconscious data collection and/or analysis +3% +3% +7% +2% -7% None of the above -1% +3% +2% +11% -2% Average number offered: +0.1 -- -0.2 -0.3 -0.8 Takeaway: Except for a +12% increase in synthetic data among service-led suppliers with 101-500 FTE, all the big changes in technology services were downward, including three among service-led with 500+ FTE: DIY surveys (-22%), online qualitative data collection (-19%), and collection and/or analysis of unstructured data (-13%). Source: GRIT 2026 Insights Practice Report, Greenbook. SERVED MARKETS BY SEGMENT | SUPPLIER POV [DATA] TOP 5 SIGNIFICANT MARKETS: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Financial services 59% 35% 62% 59% 58% Consumer packaged goods (CPG/FMCG) 69% 50% 59% 67% 57% Healthcare & pharmaceuticals 38% 37% 49% 43% 47% Technology & telecom 55% 21% 37% 50% 47% Market research, insights, or analytics 60% 38% 44% 32% 36% Media, entertainment, & sports 47% 18% 21% 37% 42% Retail & ecommerce 42% 21% 37% 61% 37% Consumer durables & home products 34% 30% 32% 41% 40% n = 39 158 79 56 55 Green shading indicates top five market. Takeaway: CPG/FMCG and financial services are the two most commonly cited significant markets across all supplier segments, and other market research, insights, and analytics providers are top five markets for tech-led and service-led suppliers with 100 or fewer FTE. Source: GRIT 2026 Insights Practice Report, Greenbook. MOST COMMON SIGNIFICANT MARKETS: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Financial services 59% 35% 62% 59% 58% Consumer packaged goods (CPG/FMCG) 69% 50% 59% 67% 57% Healthcare & pharmaceuticals 38% 37% 49% 43% 47% Technology & telecom 55% 21% 37% 50% 47% Media, entertainment, & sports 47% 18% 21% 37% 42% Consumer durables & home products 34% 30% 32% 41% 40% Retail & ecommerce 42% 21% 37% 61% 37% Market research, insights, or analytics 60% 38% 44% 32% 36% Prefer not to answer 2% 2% 1% 2% 6% Average number of markets: 5.1 3.6 4.5 5.1 5.0 n = 39 158 79 56 55 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage; excludes “other” and “prefer not to answer.” Takeaway: At least half in each segment name CPG/FMCG as a significant market, and, except for service-led suppliers with ≤20 FTE, most in each say financial services is significant. Source: GRIT 2026 Insights Practice Report, Greenbook. LESS COMMON SIGNIFICANT MARKETS: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Hospitality, travel, & leisure 27% 21% 16% 25% 35% Automotive 19% 13% 21% 30% 26% Professional & business services 18% 21% 18% 16% 23% Public sector, education, or NFP 22% 28% 27% 25% 22% Transport, logistics, & shipping 10% 7% 11% 9% 18% Industrial & manufacturing 4% 13% 13% 14% 15% Other 2% 3% -- -- -- Prefer not to answer 2% 2% 1% 2% 6% Average number of markets: 5.1 3.6 4.5 5.1 5.0 n = 39 158 79 56 55 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage; excludes “other” and “prefer not to answer.” Takeaway: Among the lesser-mentioned significant markets, hospitality, travel and leisure is named by 35% of service-led suppliers with 500+ FTE, while at least 20% in each segment name public sector, education, or NFP. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC Interpretation] GRIT’s older revenue-source supplier segments had become unstable as suppliers expanded their portfolios, and “full-service research” — the label applying to most service-led suppliers — grew too broad to be useful. The new segmentation splits tech-led from service-led and stratifies service-led by employee count. Tech-led remains structurally separate and stable, though far from pure: platforms and tools make up only about 37% of the average tech-led supplier’s offerings. The four service-led size bands show distinct strategies. Those with 500+ FTE appear to be reengineering toward higher-margin, less labor-intensive offerings such as data and analytics and away from field services and structured survey work, consistent with an effort to “right-size” overhead. Those with 101–500 FTE appear to have found a sweet spot, with robust offerings across consulting, research, field, and technology. Those with 21–100 FTE are using full-service research as a growth platform while building technology and analytics; those with ≤20 FTE sit in a more stable, specialist-heavy equilibrium. Underlying much of this, automation is reshaping cost structures — reducing the headcount that labor-intensive “traditional research” requires while letting smaller suppliers offer more without adding staff. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Insights’ Hottest Methods! This section previews the seven methodology sections to follow by focusing on which methods from our set of over 50 stand out based on current use and adoption momentum. WHICH METHODS ARE HAVING A MOMENT? [ORIENTATION] GROWTH MOMENTUM SINCE LAST YEAR: GRIT SEGMENT (AT LEAST 10% INCREASE IN THREE OR MORE SEGMENTS) Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Synthetic data +18% +13% +1% +14% +7% +18% +18% Crowdsourcing +14% +9% +13% +12% +17% +12% +13% CATI +3% +17% +11% +1% -6% +15% -14% Causal analysis -5% -7% +20% -7% -10% +26% +11% Mobile ethnography -10% +19% -4% -4% +17% +19% -7% Green shading indicates changes of at least 10%; red shading, decreases of at least 10%. Takeaway: Synthetic data and crowdsourcing usage each increased +10% or more in five or more segments; three other methods increased at least +10% among service-led suppliers with 101-500 FTE and two other segments while dropping by double digits in one. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CONTRACTION SINCE LAST YEAR: GRIT SEGMENT (AT LEAST 10% DECREASE IN THREE OR MORE SEGMENTS) Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Interviewer-administered in-person surveys -35% -1% -2% -13% -18% -6% -10% Online text- or SMS-based qual -17% +11% -6% -4% -17% -10% -18% Green shading indicates changes of at least 10%; red shading, decreases of at least 10%. Takeaway: Use of interviewer-administered in-person and online text- or SMS-based qual declined by double digits in at least four segments. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. METHOD MOMENTUM AND USAGE LEADERS | BRAND POV [DATA] CHANGES IN USAGE OF AT LEAST 10% BY FAMILY (BRAND: RESEARCH) Increased Decreased Surveys 1 3 Focus groups & IDIs 2 2 Sample 1 1 Observational research 0 2 Biometrics & neuroscience 0 0 Data & analytics 1 0 Other methodologies 1 0 Total 6 8 Takeaway: Brand-side researchers saw more methods decrease by double-digits than increase (8 vs. 6), including three decreases in survey methods. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (BRAND: RESEARCH) Increase Synthetic data 18% Crowdsourcing 14% Online communities for quant 13% Bulletin board studies 12% Online qual with webcams 11% Proprietary panels you own 10% Takeaway: Synthetic data (+18%) and crowdsourcing (+14%) led increases for brand-side researchers, followed by online communities for quant (+13%) and bulletin board studies (+12%). Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - LARGEST DECREASES IN USE SINCE LAST YEAR (BRAND: RESEARCH) Decrease Interviewer-administered in-person surveys -35% In-person qual (focus groups or IDIs) -15% Ethnography (NOT mobile) -15% Microsurveys -13% Postal/mail surveys -12% AI- or chatbot-moderated qualitative interviews or groups -11% Tools to detect sample fraud from supplier -10% Mobile ethnography -10% Takeaway: Among brand-side researchers, use of interviewer-administered in-person surveys declined the most (-35%), followed by in-person qual and ethnography (both -15%). Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (BRAND: RESEARCH) Family Methodology % Use Momentum Intensity Survey Online surveys 90% -5% 89% D&A Text analytics 68% +8% 55% FG&IDI Online qual with webcams 67% +11% 44% Sample Proprietary panels from external supplier 67% -- 57% D&A Social media and online content research 63% +4% 44% D&A Data integration 59% +6% 45% FG&IDI In-person qual 59% -11% 42% Survey Mobile first surveys 59% -5% 60% Survey Online communities for quant 58% +13% 52% Survey Mobile surveys (NOT mobile first) 53% -6% 44% FG&IDI Online communities for qual 53% -- 39% Takeaway: Among brand-side researchers’ ten most-used methods, online surveys lead with 90% usage and the highest intensity (89%); online communities for quant (+13%) and online qual with webcams (+11%) have the most momentum. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES IN USAGE OF AT LEAST 10% BY FAMILY (BRAND: ANALYTICS) Increased Decreased Surveys 4 0 Focus groups & IDIs 3 0 Sample 0 0 Observational research 3 0 Biometrics & neuroscience 0 0 Data & analytics 1 0 Other methodologies 0 0 Total 11 0 Takeaway: Brand-side analytics professionals saw 11 increases and no decreases across all method categories, led by surveys (4), focus groups/IDIs, and observational research (3 each). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (BRAND: ANALYTICS) Increase CAPI 23% Mobile ethnography 19% CATI 17% In-store/shopping observations 17% Online qual with webcams 14% Telephone qual 14% Synthetic data 13% Wearables 13% Mobile first surveys 12% Mobile surveys (NOT mobile first) 11% Online text- or SMS-based qual 11% Takeaway: Among brand-side analytics professionals, the fastest-growing methods are CAPI (+23%), mobile ethnography (+19%), CATI (+17%), and in-store/shopping observations (+17%). Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (BRAND: ANALYTICS) Family Methodology % Use Momentum Intensity D&A Data integration 88% -5% 68% Survey Online surveys 87% -5% 78% D&A Attribution analytics/single source data 87% +9% 52% D&A Social media and online content research 86% +5% 62% D&A Big Data analytics 86% -3% 71% Other Software or tools marketplaces 85% +3% 65% Survey Microsurveys 82% +7% 38% Survey Interviewer-administered in-person surveys 79% -1% 42% D&A Text analytics 77% -3% 51% Survey Mobile first surveys 76% +12% 40% Takeaway: Among brand-side analytics professionals’ ten most-used methods, data integration leads with 88% usage, online surveys lead in intensity (78%), and mobile first surveys have the most momentum (+12%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. METHOD MOMENTUM AND USAGE LEADERS | TECH-LED SUPPLIER POV [DATA] Increased Decreased Surveys 4 1 Focus groups & IDIs 2 1 Sample 0 0 Observational research 0 1 Biometrics & neuroscience 0 1 Data & analytics 3 0 Other methodologies 2 1 Total 11 5 Takeaway: Among tech-led suppliers, 11 methods increased by double digits and 4 decreased, with the most increases in surveys (4) and data and analytics (3). Source: GRIT 2026 Insights Practice Report, Greenbook. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (TECH-LED) Increase Social media and online content research 36% CAPI 24% Causal analysis 20% In-person qual 18% Crowdsourcing 13% Online surveys 13% Meta-analysis 13% Mobile surveys (NOT mobile first) 13% Online communities for qual 12% CATI 11% Talent marketplaces 10% Takeaway: Among tech-led suppliers, use of social media and online content research (+36%), CAPI (+24%), and causal analysis (+20) increased the most. Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - LARGEST DECREASES IN USE SINCE LAST YEAR (TECH-LED) Decrease Automated measures/people meters -15% Online qual with webcams -13% Prediction markets -12% Eye tracking -12% Postal/mail surveys -10% Takeaway: Among tech-led suppliers, automated measures/people meters (-15%), online qual with webcams (-13%), prediction markets (-12%), eye tracking (-12%), and postal/mail surveys (-10%) decreased by double digits. Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (TECH-LED) Family Methodology % Use Momentum Intensity Survey Online surveys 88% +13% 79% D&A Text analytics 82% -1% 62% Sample Proprietary panels from external supplier 71% +2% 69% Other Sample marketplaces 70% +1% 72% D&A Social media and online content research 69% +36% 27% Sample In-house tools to detect sample fraud 68% -4% 84% Survey Mobile first surveys 66% +2% 84% Sample Tools to detect sample fraud from supplier 61% +4% 78% Survey Mobile surveys (NOT mobile first) 60% +13% 62% Survey Online communities for quant 57% +8% 71% Takeaway: Among tech-led suppliers’ ten most-used methods, online surveys leads with 88% usage, in-house tools to detect sample fraud and mobile first surveys are the most intense (84% each), and social media and online content research has the most momentum (+36%). Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD MOMENTUM AND USAGE LEADERS | SERVICE-LED: 500+ FTE POV [DATA] CHANGES IN USAGE OF AT LEAST 10% BY FAMILY (SERVICE-LED: 500+ FTE) Increased Decreased Surveys 0 7 Focus groups & IDIs 1 1 Sample 1 1 Observational research 1 1 Biometrics & neuroscience 1 1 Data & analytics 4 1 Other methodologies 1 0 Total 9 12 Takeaway: Among service-led suppliers with 500+ FTE, 9 methods increased by double digits and 12 decreased, with the most increases in data and analytics (4) and the most decreases in surveys (7). Source: GRIT 2026 Insights Practice Report, Greenbook. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (SERVICE-LED: 500+ FTE) Increase Ethnography (NOT mobile) 20% Synthetic data 18% Neuroscience 17% AI- or chatbot-moderated qualitative interviews or groups 14% Crowdsourcing 13% In-house tools to detect sample fraud 13% Causal analysis 11% Big Data analytics 10% Social media and online content research 10% Takeaway: Among service-led suppliers with 500+ FTE, use of non-mobile ethnography (+20%), synthetic data (+18%), and neuroscience (+17%) increased the most. Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - LARGEST DECREASES IN USE SINCE LAST YEAR (SERVICE-LED: 500+ FTE) Decrease IVR -20% Online text- or SMS-based qual (focus groups or IDIs) -18% Mobile surveys (NOT mobile first) -16% CATI -14% CAPI -13% Sensory research or testing -12% Attribution analytics/single source data -12% Programmatic sampling -12% Microsurveys -11% Chatbot-style surveys -11% In-store/shopping observations -10% Takeaway: Among service-led suppliers with 500+ FTE, use of IVR (-20%), online text- or SMS-based qual (-18%), and mobile surveys that are not mobile first (-16%) decreased the most. Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (SERVICE-LED: 500+ FTE) Family Methodology % Use Momentum Intensity Survey Online surveys 100% +4% 88% D&A Text analytics 91% -- 67% Sample Proprietary panels from external supplier 87% -4% 68% FG&IDI Online qual with webcams 81% +3% 59% Sample In-house tools to detect sample fraud 81% +13% 79% Survey Mobile first surveys 80% -3% 78% D&A Social media and online content research 80% +10% 46% Sample Tools to detect sample fraud from supplier 76% -5 68% FG&IDI In-person qual 74% -5% 53% Obs Ethnography (NOT mobile) 74% +20% 33% Takeaway: Among service-led suppliers with 500+ FTE’s ten most-used methods, online surveys leads with 100% and is the most intense (88%), and in-house tools to detect sample fraud has the most momentum (+13%). Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD MOMENTUM AND USAGE LEADERS | SERVICE-LED: 101-500 FTE POV [DATA] CHANGES IN USAGE OF AT LEAST 10% BY FAMILY (SERVICE-LED: 101-500 FTE) Increased Decreased Surveys 4 1 Focus groups & IDIs 3 2 Sample 2 0 Observational research 3 0 Biometrics & neuroscience 1 0 Data & analytics 5 0 Other methodologies 1 1 Total 19 4 Takeaway: Among service-led suppliers with 101-500 FTE, 19 methods increased by double digits while 4 decreased, with the most increases in data and analytics�(5). Source: GRIT 2026 Insights Practice Report, Greenbook. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (SERVICE-LED: 101-500 FTE) Increase Big Data analytics 29% Causal analysis 26% Meta-analysis 23% Automated measures/people meters 20% Ethnography (NOT mobile) 20% Mobile ethnography 19% Bulletin board studies 18% Microsurveys 18% Synthetic data 18% Online communities for qual 16% In-house tools to detect sample fraud 16% Takeaway: Among service-led suppliers with 101-500 FTE, use of Big Data analytics (+29%), causal analysis (+26%), and meta-analysis (+23%) increased the most. Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - ADDITIONAL INCREASES IN USE SINCE LAST YEAR (SERVICE-LED: 101-500 FTE) Increase CATI 15% Data integration 15% Social media recruiting 15% Mobile diaries/journaling 14% Crowdsourcing 12% Neuroscience 10% Mobile first surveys 10% IVR 10% Takeaway: Among service-led suppliers with 101-500 FTE, eight methods increased between +10 and +15%. Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - LARGEST DECREASES IN USE SINCE LAST YEAR (SERVICE-LED: 101-500 FTE) Decrease Online qual with webcams -11% Online text- or SMS-based qual -10% Sample marketplaces -10% Online communities for quant -10% Takeaway: Among service-led suppliers with 101-500 FTE, use of online qual with webcams (-11%), online text- or SMS-based qual (-10%), sample marketplaces (-10%), and online communities for quant (-10%) decreased by double digits. Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (SERVICE-LED: 101-500 FTE) Family Methodology % Use Momentum Intensity Survey Online surveys 100% +1% 98% Sample Proprietary panels from external supplier 88% +6% 79% Survey Mobile first surveys 86% +10% 68% Sample In-house tools to detect sample fraud 85% +16% 84% D&A Data integration 80% +15% 37% Survey Mobile surveys (NOT mobile first) 76% -4% 57% FG&IDI Online qual with webcams 74% -11% 68% FG&IDI Bulletin board studies 73% +18% 48% Sample Tools to detect sample fraud from supplier 73% +3% 88% FG&IDI In-person qual 73% +4% 69% Takeaway: Among service-led suppliers with 101-500 FTE, online surveys leads with 100% usage and 98% intensity, and bulletin board studies has the most momentum (+18%) in the top ten. Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD MOMENTUM AND USAGE LEADERS | SERVICE-LED: 21-100 FTE POV [DATA] CHANGES IN USAGE OF AT LEAST 10% BY FAMILY (SERVICE-LED: 21-100 FTE) Increased Decreased Surveys 0 1 Focus groups & IDIs 1 1 Sample 2 1 Observational research 1 1 Biometrics & neuroscience 0 0 Data & analytics 0 1 Other methodologies 1 0 Total 5 4 Takeaway: Among service-led suppliers with 21-100 FTE, 5 methods increased by double digits while 4 decreased with increases and decreases spread across categories. Source: GRIT 2026 Insights Practice Report, Greenbook. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (SERVICE-LED: 21-100 FTE) Increase AI-/chatbot-moderated qual 20% Crowdsourcing 17% Mobile ethnography 17% Programmatic sampling 14% Proprietary panels you own 13% Takeaway: Among service-led suppliers with 21-100 FTE, use of AI-/chatbot-moderated qual (+20%), crowdsourcing (+17%), and mobile ethnography (+17%) increased most. Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - LARGEST DECREASES IN USE SINCE LAST YEAR (SERVICE-LED: 21-100 FTE) Decrease Interviewer-administered in-person surveys -18% Online text- or SMS-based qual (focus groups or IDIs) -17% Attribution analytics/single source data -13% Social media recruiting -10% Causal analysis -10% Takeaway: Among service-led suppliers with 21-100 FTE, use of interviewer-administered in-person surveys (-18%), online text- or SMS-based qual (-17%), attribution analytics/single source data (-13%), social media recruiting (-10%), and causal analysis (-10%) decreased by double digits. Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (SERVICE-LED: 21-100 FTE) Family Methodology % Use Momentum Intensity Survey Online surveys 97% -1% 99% Sample Proprietary panels from external supplier 86% +8% 64% D&A Text analytics 76% +4% 59% Sample Tools to detect sample fraud from supplier 74% +9% 72% FG&IDI Online qual with webcams (focus groups or IDIs) 74% +4% 77% Sample In-house tools to detect sample fraud 73% +5% 80% Survey Mobile surveys (NOT mobile first) 68% -1% 64% Other Sample marketplaces 68% +2% 71% Survey Mobile first surveys 65% +1% 76% FG&IDI In-person qual (focus groups or IDIs) 60% +5% 61% Takeaway: Among service-led suppliers with 21-100 FTE, online surveys leads with 97% usage and 99% intensity, and tools to detect sample fraud from supplier has the most momentum (+9%) in the top ten. Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD MOMENTUM AND USAGE LEADERS | SERVICE-LED: ≤20 FTE POV [DATA] CHANGES IN USAGE OF AT LEAST 10% BY FAMILY (SERVICE-LED: ≤20 FTE) Increased Decreased Surveys 0 1 Focus groups & IDIs 0 0 Sample 1 0 Observational research 0 0 Biometrics & neuroscience 0 0 Data & analytics 0 1 Other methodologies 2 0 Total 3 2 Takeaway: Among service-led suppliers with ≤20 FTE, 3 methods increased by double digits while 2 decreased with increases and decreases spread across categories. Source: GRIT 2026 Insights Practice Report, Greenbook. MOMENTUM - LARGEST INCREASES IN USE SINCE LAST YEAR (SERVICE-LED: ≤20 FTE) Increase Tools to detect sample fraud from supplier 13% Talent marketplaces 13% Crowdsourcing 12% Takeaway: Among service-led suppliers with ≤20 FTE, use of tools to detect sample fraud from supplier (+13%), talent marketplaces (+13%), and crowdsourcing (+12%) increased the most. Source: GRIT 2026 Insights Practice Report, Greenbook MOMENTUM - LARGEST DECREASES IN USE SINCE LAST YEAR (SERVICE-LED: ≤20 FTE) Decrease Attribution analytics/single source data -13% Interviewer-administered in-person surveys -13% Causal analysis -10% Takeaway: Among service-led suppliers with ≤20 FTE, use of attribution analytics/single source data (-13%), interviewer-administered in-person surveys (-13%), and causal analysis (-10%) decreased by double digits. Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 METHODS IN USE (SERVICE-LED: ≤20 FTE) Family Methodology % Use Momentum Intensity Survey Online surveys 83% -4% 77% D&A Text analytics 76% +4% 50% Sample Proprietary panels from external supplier 73% +3% 67% FG&IDI Online qual with webcams (focus groups or IDIs) 69% +4% 76% FG&IDI In-person qual (focus groups or IDIs) 62% -2% 56% Other Sample marketplaces 59% +6% 66% Survey Mobile surveys (NOT mobile first) 58% +5% 43% Sample Tools to detect sample fraud from supplier 57% +13% 73% Survey Mobile first surveys 56% +1% 42% Survey Interviewer-administered in-person surveys 55% -13% 51% Takeaway: Among service-led suppliers with ≤20 FTE, online surveys leads with 83% usage and 77% intensity, and tools to detect sample fraud from supplier has the most momentum (+13%) in the top ten. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC Interpretation] Viewed across all seven methodology families at once, patterns emerge that no single section shows. Only crowdsourcing and synthetic data have genuine cross-segment momentum, each rising by double digits in five or more segments; every other gaining method is concentrated in specific segments or families. Interviewer-administered in-person surveys and online text-based qual are the broadest decliners. Among brand-side researchers, the methods gaining share a common trait — they can be executed with minimal external dependency (owned panels, online communities, asynchronous boards, synthetic data, crowdsourcing) — while the methods declining require external infrastructure or physical presence. The brand-side analytics segment is expanding unusually broadly (eleven increases, zero decreases, across five families), including methods historically associated with researchers. On the supplier side, methodological change scales with size, and the standout is service-led suppliers with 101–500 FTE: nineteen increases against four decreases, eleven of them above +15%, spread across five families — no other segment approaches this scale of simultaneous expansion. Service-led suppliers with 500+ FTE move the opposite way on surveys (zero increases against seven decreases), adding analytical and observational depth while shedding operational overhead. The industry is not moving uniformly in one direction. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Survey Research In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across eleven survey research methods. ARE ONLINE SURVEYS STILL UBIQUITOUS? [ORIENTATION] PROJECT ALLOCATION ACROSS QUANT AND QUAL: GRIT SEGMENT Quant only Qual only Both quant & qual Neither qual nor quant Brand: research (n = 170) 45% 24% 28% 4% Brand: analytics (n = 148) 33% 24% 39% 4% Tech-led (n = 35) 53% 24% 18% 5% Service-led: ≤20 FTE (n = 149) 47% 29% 22% 2% Service-led: 21-100 FTE (n = 77) 52% 24% 22% 2% Service-led: 101-500 FTE (n = 55) 46% 25% 26% 3% Service-led: 500+ FTE (n = 53) 48% 19% 25% 8% Takeaway: Across segments, 69% to 74% of projects include quant, while qual ranges from 42% (tech-led suppliers) to 63% (brand-side analytics); brand-side analytics has the highest percentage of qualiquant projects (39%). Source: GRIT 2026 Insights Practice Report, Greenbook THREE MOST-USED METHODS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online surveys 90% 87% 88% 83% 97% 100% 100% Mobile first surveys 59% 76% 66% 56% 65% 86% 80% Online communities for quant 58% 61% 57% 37% 46% 56% 70% Mobile surveys (NOT mobile first) 53% 72% 60% 58% 68% 76% 64% Interviewer-admin in-person 43% 79% 26% 55% 48% 57% 61% Microsurveys 42% 82% 52% 26% 32% 56% 51% Green shading indicates top three most-used methodologies. Takeaway: Online surveys are the most-used survey method in each segment, and mobile first surveys are among the top three in all but brand-side analytics (76%) where microsurveys (79%) and interviewer-admin in-person surveys (82%) are more prominent. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online communities for quant +13% -1% +8% -1% -2% -10% -1% Chatbot-style surveys +8% -- +2% +4% -1% +6% -11% CAPI +6% +23% +24% -4% +5% +8% -13% CATI +3% +17% +11% +1% -6% +15% -14% IVR +3% +5% +7% +4% +4% +10% -20% Online surveys -5% -5% +13% -4% -1% +1% +4% Mobile first surveys -5% +12% +2% +1% +1% +10% -3% Mobile surveys (NOT mobile first) -6% +11% +13% +5% -1% -4% -16% Postal/mail surveys -12% -9% -10% -3% -2% -1% +7% Microsurveys -13% +7% +9% -7% +1% +18% -11% Interviewer-admin in-person -35% -1% -2% -13% -18% -6% -9% Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: CAPI increased at least +5% in five segments, while interviewer-administered in-person surveys fell at least -5% in five segments. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 SURVEY METHODS 2026 Method 2025 Precedent 2025 Family CATI (Computer-assisted Telephone Interviewing) CATI (Computer-assisted Telephone Interviewing) Surveys Chatbot-style surveys Chatbots Surveys Computer/tablet-assisted in-person surveys (CAPI) CAPI (Computer-assisted Personal Interviewing) Surveys Interviewer-administered in-person surveys Face-to-face interviews Surveys IVR (Interactive Voice Response) IVR (Interactive Voice Response) Surveys Microsurveys Microsurveys Surveys Mobile first surveys Mobile first surveys Surveys Mobile surveys (NOT mobile first) Mobile surveys (NOT mobile first) Surveys Online communities for quant Online communities for quant Surveys Online surveys Online surveys Surveys Postal/mail surveys Mail surveys Surveys Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS |BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT Research Analytics Research – analytics Online surveys 90% 87% +3% Mobile first surveys 59% 76% -17% Online communities for quant 58% 61% -3% Mobile surveys (NOT mobile first) 53% 72% -19% Interviewer-admin in-person 43% 79% -36% Microsurveys 42% 82% -40% CAPI 32% 67% -35% CATI 28% 50% -22% Chatbot-style surveys 27% 64% -37% IVR 15% 48% -33% Postal/mail surveys 15% 49% -34% Average number used: 4.6 7.4 -2.8 n (range) = 104-118 84-106 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more survey methods than researchers on average (7.4 vs. 4.6), with the largest gaps in microsurveys (82% vs. 42%), chatbot-style surveys (64% vs. 27%), and interviewer-administered in-person (79% vs. 43%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 80% 10% 9% 0% 1% Mobile first surveys 35% 23% 31% 9% 1% Online communities for quant 30% 27% 18% 21% 3% Microsurveys 18% 24% 34% 18% 6% Mobile surveys (NOT mobile first) 23% 30% 22% 20% 4% Chatbot-style surveys 6% 21% 34% 35% 4% Interviewer-admin in-person 16% 27% 15% 39% 3% CAPI 12% 20% 20% 44% 4% CATI 12% 16% 13% 54% 5% IVR 5% 10% 14% 56% 15% Postal/mail surveys 5% 9% 6% 78% 1% n (range) = 104-118 Takeaway: Among brand-side researchers, the survey methods with the most potential are chatbot-style surveys (only 44% of probable users are current users), IVR (51%), and microsurveys (55%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A – 25A Online surveys 98% 99% 94% 94% 96% 95% 90% -5% Mobile first surveys 52% 50% 48% 64% 69% 63% 59% -4% Online communities for quant 72% 67% 64% 47% 46% 44% 58% +14% Mobile surveys (NOT mobile first) 88% 83% 80% 67% 63% 60% 53% -7% Interviewer-admin in-person 56% 52% 38% 68% 62% 78% 43% -35% Microsurveys 39% 33% 28% 55% 49% 55% 42% -13% CAPI 38% 40% 29% 29% 31% 26% 32% +6% CATI 46% 45% 35% 34% 19% 25% 28% +3% Chatbot-style surveys 17% 15% 20% 21% 24% 19% 27% +8% IVR 18% 21% 13% 13% 11% 12% 15% +3% Postal/mail surveys 29% 23% 19% 24% 19% 27% 15% -12% Average number used: 5.5 5.3 4.7 5.2 4.9 5.0 4.6 -0.4 n (minimum) = 285-298 207-209 182-188 214 190 121-141 104-118 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side researchers, online surveys (90%) is perennially the most-used method; use of mobile first surveys increased from 44% to 58% while use of interviewer-administered in-person fell from 78% to 43%, microsurveys fell from 55% to 42%, and postal/mail surveys fell from 27% to 15%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 68% 19% 13% 0% 0% Mobile surveys (NOT mobile first) 26% 46% 24% 4% 0% Microsurveys 31% 51% 13% 4% 1% Mobile first surveys 30% 46% 17% 4% 2% Interviewer-admin in-person 33% 46% 12% 9% 0% Chatbot-style surveys 29% 35% 27% 9% 0% CAPI 21% 46% 22% 10% 1% Online communities for quant 17% 44% 23% 16% 0% IVR 18% 30% 29% 19% 4% CATI 16% 34% 16% 29% 5% Postal/mail surveys 17% 32% 11% 38% 2% n (range) = 84-106 Takeaway: Among brand-side analytics professionals, the survey method with the most potential is IVR (62%); for every other method, at least 70% of probable users use them currently. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Online surveys 86% 91% 92% 87% -5% Microsurveys 65% 57% 75% 82% +7% Interviewer-admin in-person 74% 73% 80% 79% -1% Mobile first surveys 54% 60% 65% 76% +11% Mobile surveys (NOT mobile first) 58% 54% 61% 72% +11% CAPI 30% 35% 44% 67% +23% Chatbot-style surveys 43% 50% 64% 64% -- Online communities for quant 47% 55% 62% 61% -1% CATI 34% 36% 33% 50% +17% Postal/mail surveys 45% 49% 59% 49% -10% IVR 31% 35% 43% 48% +5% Average number used: 5.7 6.0 6.8 7.4 +0.6 n = 183 194 95 84-106 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among analytics professionals, online surveys (87%) is perennially the most-used method; use of CAPI increased from 44% to 67%; CATI, from 33% to 50%; mobile first surveys, from 65% to 76%; and mobile surveys (not mobile first), from 61% to 72%. Use of postal/mail surveys fell from 59% to 49%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics Online surveys 89% 78% Mobile first surveys 60% 40% Online communities for quant 52% 27% Mobile surveys (NOT mobile first) 44% 37% CATI 43% 32% Microsurveys 43% 38% Interviewer-administered in-person surveys 37% 42% CAPI 37% 31% Postal/mail surveys 35% 35% IVR 34% 38% Chatbot-style surveys 23% 45% n (range) = 104-118 91-106 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side insights professionals who use online surveys use them regularly; among brand-side researchers, most users of mobile first surveys (60%) and online communities for quant (52%) use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online surveys 88% 83% 97% 100% 100% Mobile first surveys 66% 56% 65% 86% 80% Online communities for quant 57% 37% 46% 56% 70% Mobile surveys (NOT mobile first) 60% 58% 68% 76% 64% Interviewer-admin in-person 26% 55% 48% 57% 61% CAPI 43% 38% 48% 54% 57% CATI 39% 38% 39% 52% 52% Microsurveys 52% 26% 32% 56% 51% Chatbot-style surveys 40% 14% 24% 36% 36% Postal/mail surveys 11% 12% 30% 22% 32% IVR 22% 9% 21% 20% 17% Average number used: 5.0 4.3 5.2 6.1 6.2 n (range) = 23-28 93-112 48-55 33-43 30-42 Green shading indicates top three most-used methodologies. Takeaway: Online and mobile first surveys are among the top three most-used in each supplier segment; mobile surveys that are not mobile first are also in the top three for all segments but service-led suppliers with 500+FTE where online communities for quant (70%) is third. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online surveys 79% 77% 99% 98% 88% IVR 10% 10% 32% 0% 82% Mobile first surveys 84% 42% 76% 68% 78% Mobile surveys (NOT mobile first) 62% 43% 64% 57% 70% CATI 22% 20% 64% 52% 52% Online communities for quant 71% 27% 54% 35% 45% Microsurveys 39% 26% 34% 27% 44% Postal/mail surveys 0% 31% 40% 28% 44% Interviewer-admin in-person 21% 51% 42% 49% 43% CAPI 67% 37% 55% 53% 41% Chatbot-style surveys 23% 18% 34% 26% 29% n (range) = 23-28 93-112 48-55 33-43 30-42 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: In each supplier segment, most users of online surveys use them regularly; the same is true in at least three segments each for mobile first surveys, mobile surveys that are not mobile first, and CATI. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 70% 18% 8% 4% 0% Microsurveys 20% 31% 28% 12% 8% Mobile first surveys 55% 10% 10% 24% 0% Mobile surveys (NOT mobile first) 37% 23% 13% 24% 3% Chatbot-style surveys 9% 31% 32% 27% 0% Online communities for quant 41% 16% 4% 39% 0% CAPI 29% 14% 9% 48% 0% CATI 9% 30% 12% 49% 0% IVR 2% 20% 24% 48% 6% Interviewer-admi in-person 6% 21% 9% 65% 0% Postal/mail surveys 0% 11% 6% 84% 0% n (range) = 23-28 Takeaway: Among tech-led suppliers, the survey method with the most potential is IVR (only 48% who will probably use it currently do), followed by chatbot-style surveys (55%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online surveys 91% 91% 86% 89% 87% 75% 88% +13% Mobile first surveys 63% 68% 68% 74% 59% 64% 66% +2% Mobile surveys (NOT mobile first) 87% 91% 79% 60% 50% 48% 60% +12% Online communities for quant 62% 61% 58% 49% 54% 49% 57% +8% Microsurveys 36% 46% 35% 47% 37% 43% 52% +9% CAPI 40% 20% 24% 34% 35% 19% 43% +24% Chatbot-style surveys 14% 28% 27% 21% 26% 38% 40% +2% CATI 43% 26% 22% 26% 40% 28% 39% +11% Interviewer-admin in-person 30% 26% 20% 37% 40% 28% 26% -2% IVR 23% 13% 10% 14% 13% 15% 22% +7% Postal/mail surveys 24% 11% 17% 25% 25% 21% 11% -10% Average number used: 5.1 4.8 4.4 4.8 4.6 4.3 5.0 +0.7 n (range) = 90-97 46-50 122-125 70 34-44 29-38 23-28 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among tech-led suppliers, online surveys (88%) is perennially the most-used method and mobile first surveys (66%) is also in the top three; use of CAPI increased from 19% to 43%; online surveys, from 75% to 88%; mobile surveys that are not mobile first, 48% to 60%; and CATI, 28% to 39%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 88% 12% 0% 0% 0% Mobile first surveys 63% 18% 9% 6% 5% Online communities for quant 32% 39% 15% 15% 0% Chatbot-style surveys 11% 25% 41% 19% 4% CAPI 23% 33% 20% 23% 0% Microsurveys 22% 28% 26% 14% 10% Mobile surveys (NOT mobile first) 45% 19% 11% 21% 4% Interviewer-admin in-person 26% 35% 8% 29% 2% CATI 27% 25% 7% 37% 3% IVR 14% 3% 29% 48% 6% Postal/mail surveys 14% 18% 2% 61% 5% n (range) = 30-42 Takeaway: Among service-led suppliers with 500+ FTE, the survey method with the most potential is IVR (only 37% who will probably use it currently do), followed by chatbot-style surveys (46%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online surveys 99% 98% 94% 95% 97% 96% 100% +4% Mobile first surveys 75% 68% 68% 73% 72% 83% 80% -3% Online communities for quant 78% 69% 79% 60% 68% 72% 70% -2% Mobile surveys (NOT mobile first) 96% 93% 91% 74% 73% 80% 64% -16% Interviewer-admin in-person 65% 63% 49% 68% 70% 71% 61% -10% CAPI 64% 59% 53% 57% 62% 70% 57% -13% CATI 69% 64% 59% 60% 65% 66% 52% -14% Microsurveys 44% 35% 41% 59% 62% 62% 51% -11% Chatbot-style surveys 27% 22% 21% 26% 30% 47% 36% -11% Postal/mail surveys 38% 32% 33% 27% 30% 25% 32% +7% IVR 38% 30% 31% 18% 30% 37% 17% -20% Average number used: 6.9 6.3 6.2 6.2 6.6 7.1 6.2 -0.9 n (range) = 104-106 85-88 117-129 97 58-78 53-71 30-42 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 500+ FTE, online surveys (100%) is perennially the most-used method and mobile first surveys (80%) has been in the top three for four straight years; use of seven survey methods decreased by double digits, led by IVR (37% to 17%) and mobile surveys that are not mobile first (80% to 64%). Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 98% 2% 0% 0% 0% Mobile first surveys 59% 28% 12% 0% 2% Mobile surveys (NOT mobile first) 43% 33% 11% 6% 6% Online communities for quant 19% 37% 23% 19% 2% Chatbot-style surveys 9% 26% 38% 23% 3% Microsurveys 15% 41% 16% 12% 17% Interviewer-admin in-person 28% 29% 8% 33% 2% CAPI 29% 25% 10% 30% 6% CATI 27% 25% 4% 42% 3% IVR 0% 20% 19% 38% 23% Postal/mail surveys 6% 16% 2% 70% 6% n (range) = 33-43 Takeaway: Among service-led suppliers with 101-500 FTE, the survey methods with the most potential are IVR (only 51% who will probably use it currently do) and chatbot-style surveys (48%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online surveys 95% 99% 94% 98% 98% 99% 100% +1% Mobile first surveys 72% 72% 74% 76% 72% 76% 86% +10% Mobile surveys (NOT mobile first) 94% 94% 93% 76% 72% 80% 76% -4% Interviewer-admin in-person 69% 60% 51% 72% 66% 63% 57% -6% Online communities for quant 79% 68% 73% 64% 60% 66% 56% -10% Microsurveys 31% 31% 33% 48% 43% 37% 56% +19% CAPI 56% 53% 52% 50% 43% 46% 54% +8% CATI 66% 64% 65% 59% 33% 36% 52% +16% Chatbot-style surveys 19% 15% 18% 12% 26% 30% 36% +6% Postal/mail surveys 47% 36% 36% 27% 36% 23% 22% -1% IVR 24% 28% 27% 14% 20% 10% 20% +10% Average number used: 6.5 6.2 6.2 6.0 5.7 5.7 6.1 +0.4 n (range) = 108 81-89 127-134 102 54-78 45-63 33-43 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 101-500 FTE, online surveys (100%) is perennially the most-used method, mobile surveys that are not mobile first (76%) have also been in the top three every year, and mobile first surveys (86%) have been in the top three for the last six years; use of microsurveys increased from 37% to 56% and CATI increased from 36% to 52%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 96% 1% 3% 0% 0% Mobile surveys (NOT mobile first) 44% 24% 18% 11% 3% Mobile first surveys 50% 16% 17% 12% 7% Online communities for quant 25% 21% 33% 18% 4% Chatbot-style surveys 8% 16% 45% 26% 5% Interviewer-admin in-person 20% 28% 13% 39% 0% CAPI 26% 22% 12% 38% 2% CATI 25% 14% 17% 41% 3% Microsurveys 11% 21% 23% 30% 15% Postal/mail surveys 12% 18% 6% 64% 0% IVR 7% 15% 12% 51% 15% n (range) = 48-55 Takeaway: Among service-led suppliers with 21-100 FTE, the survey methods with the most potential are chatbot-style surveys (only 35% who will probably use it currently do), online communities for quant (58%), and microsurveys (58%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online surveys 98% 97% 90% 95% 96% 99% 97% -2% Mobile surveys (NOT mobile first) 93% 91% 80% 71% 70% 69% 68% -1% Mobile first surveys 64% 62% 56% 65% 72% 64% 65% +1% CAPI 53% 51% 50% 50% 55% 43% 48% +5% Interviewer-admin in-person 62% 57% 53% 68% 71% 65% 48% -17% Online communities for quant 66% 61% 59% 59% 55% 48% 46% -2% CATI 58% 63% 60% 60% 63% 45% 39% -6% Microsurveys 37% 32% 26% 47% 44% 31% 32% +1% Postal/mail surveys 36% 40% 28% 30% 42% 32% 30% -2% Chatbot-style surveys 14% 14% 19% 13% 26% 25% 24% -1% IVR 26% 23% 24% 24% 17% 17% 21% +4% Average number used: 6.0 5.9 5.5 5.8 6.1 5.4 5.2 -0.2 n (range) = 163-169 122-130 142-145 184 90-109 75-93 48-55 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 21-100 FTE, online surveys (97%) is perennially the most-used method, and mobile surveys that are not mobile first (68%) have been in the top three every year but one; use of interviewer-administered in-person fell from 65% to 48%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online surveys 64% 20% 10% 6% 1% Mobile surveys (NOT mobile first) 25% 33% 24% 14% 4% Mobile first surveys 24% 32% 16% 23% 5% Interviewer-admin in-person 28% 27% 15% 29% 1% Online communities for quant 10% 27% 17% 43% 3% CATI 8% 30% 16% 45% 1% Microsurveys 7% 19% 24% 39% 12% CAPI 14% 24% 11% 48% 3% Chatbot-style surveys 3% 12% 30% 50% 6% IVR 1% 8% 10% 67% 14% Postal/mail surveys 4% 8% 7% 77% 5% n (range) = 93-112 Takeaway: Among service-led suppliers with ≤20 FTE, the survey methods with the most potential are chatbot-style surveys (only 32% who will probably use it currently do), IVR (48%), and microsurveys (52%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online surveys 96% 97% 86% 90% 79% 87% 83% -4% Mobile surveys (NOT mobile first) 86% 89% 76% 64% 50% 53% 58% +5% Mobile first surveys 43% 43% 47% 56% 52% 55% 56% +1% Interviewer-admin in-person 60% 53% 44% 74% 64% 68% 55% -13% CATI 62% 54% 51% 47% 41% 37% 38% +1% CAPI 45% 48% 41% 41% 42% 42% 38% -4% Online communities for quant 52% 58% 51% 40% 46% 38% 37% -1% Microsurveys 30% 26% 30% 34% 25% 32% 26% -6% Chatbot-style surveys 4% 6% 7% 9% 3% 10% 14% +4% Postal/mail surveys 25% 25% 21% 20% 11% 15% 12% -3% IVR 17% 13% 13% 6% 8% 5% 9% +4% Average number used: 5.2 5.1 4.7 4.8 4.2 4.4 4.3 -0.1 n (range) = 267-310 194-221 234-239 271 106-139 124-146 93-112 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with ≤20 FTE, online surveys (83%) is perennially the most-used method, mobile surveys that are not mobile first (58%) have been in the top three every year but two, and mobile first surveys (56%) have been in the top three the last three years; interviewer-administered in-person fell from 68% to 55%. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC Interpretation] Online surveys remain the most-used method in every segment, with saturation at 91% among brand-side researchers — little room left to grow. The rest of the survey portfolio, however, is being reconfigured around cost. Among researchers, online communities for quant surged +14% to 58%, returning to the top three after a three-year absence, while interviewer-administered in-person surveys plunged −35% to 43% after three years above 60%; relabeling explains only part of the in-person drop, and the shift is consistent with shrinking budgets favoring lower-cost, scalable alternatives. Among service-led suppliers with 500+ FTE, seven survey methods fell by double digits, leaving little beyond online surveys, mobile-first, and online communities — a pattern that fits the cost-structure reengineering seen elsewhere in these segments; the parallel rises among 101–500 FTE suppliers (microsurveys +19%, CATI +16%) suggest capacity migrating down a size band. On the brand side, analytics professionals run a broad, boundary-straddling portfolio averaging 7.4 methods versus 4.6 for researchers, who instead rely intensely on a small core. CAPI is quietly rising, posting some of the dataset’s largest single-wave increases, perhaps reflecting demand for in-person rigor with digital-capture efficiency. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Focus Groups & IDI’s In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across nine focus group, IDI, and related qualitative methods. HOW IS AI CHANGING QUALITATIVE RESEARCH? [ORIENTATION] THREE MOST-USED METHODS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online qual with webcams 67% 63% 39% 69% 74% 74% 81% In-person qual 59% 73% 39% 62% 60% 73% 74% Online communities for qual 53% 67% 45% 45% 55% 70% 72% Telephone qual 31% 64% 25% 35% 48% 52% 43% Mobile qual 41% 50% 41% 46% 52% 61% 63% Bulletin board studies 36% 50% 31% 37% 51% 73% 56% n (range) = 104-133 85-105 20-27 88-109 46-56 33-39 30-45 Green shading indicates top three most-used methodologies. Takeaway: In-person qual is a top-three method in each segment, online qual with webcams is top-three in all but brand-side analytics (63%), and online communities for qual is top-three in five segments. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Bulletin board studies +12% +4% +7% -2% -2% +18% +6% Online qual with webcams +11% +14% -13% +4% +4% -11% +3% Online communities for qual 0% +6% +12% -2% -2% +16% -7% Online text- or SMS-based qual -1% +11% -6% -4% -17% -10% -18% Mobile qual -2% +3% +1% -2% -7% +5% -5% Telephone qual -8% +14% +1% -5% +8% -8% +1% Mobile diaries/journaling -9% +2% +8% -9% -3% +14% -9% AI-/chatbot-moderated qual -11% -9% 0% +1% +20% +5% +14% In-person qual -11% +9% +18% -2% +5% +4% -5% n (range) = 104-133 85-105 20-27 88-109 46-56 33-39 30-45 Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: Usage of bulletin board studies (online discussion boards) increased at least +5% in four segments while online text- or SMS-based qual fell at least -5% in four; in-person qual, AI- or chatbot-moderated qual, and online communities for qual each increased at least +5% in three segments. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 FOCUS GROUP & IDI METHODS 2026 Method 2025 Precedent 2025 Family AI- or chatbot-moderated qualitative interviews or groups (online) NEW (partly anticipated by ‘Automated interviewing via AI systems’) N/A Bulletin board studies (online discussion boards) Bulletin board studies Observational In-person qual (focus groups or IDIs) In-person qual (focus groups or IDIs) Focus Groups & IDIs Mobile diaries/journaling Mobile diaries/journaling Observational Mobile qual (focus groups or IDIs) Mobile qual (focus groups or IDIs) Focus Groups & IDIs Online communities for qual Online communities for qual Focus Groups & IDIs Online qual with webcams (focus groups or IDIs) Online qual with webcams (focus groups or IDIs) Focus Groups & IDIs Online text- or SMS-based qual (focus groups or IDIs) Chat (text-based) online qual (focus groups or IDIs) Focus Groups & IDIs Telephone qual (focus groups or IDIs) Telephone qual (focus groups or IDIs) Focus Groups & IDIs Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT BRAND Research Analytics Research - analytics Online qual with webcams 67% 63% +4% In-person qual 59% 73% -14% Online communities for qual 53% 67% -14% Mobile qual 41% 50% -9% Bulletin board studies 36% 50% -14% Mobile diaries/journaling 36% 42% -6% AI-/chatbot-moderated qual 33% 55% -22% Online text- or SMS-based qual 32% 59% -27% Telephone qual 31% 64% -33% Average number used: 3.9 5.2 -1.3 n (range) = 104-133 85-105 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more methods for focus groups and IDIs, on average, than researchers (5.2 vs. 3.9), with the largest gaps in telephone qual (64% vs. 31%), online text- or SMS-based qual (59% vs. 32%), and AI-/chatbot-moderated qual (55% vs. 33%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online qual with webcams 29% 38% 21% 9% 3% In-person qual 24% 34% 25% 17% 0% Online communities for qual 20% 32% 23% 24% 0% AI-/chatbot-moderated qual 10% 23% 36% 28% 3% Mobile qual 17% 24% 26% 30% 3% Bulletin board studies 5% 31% 25% 37% 2% Mobile diaries/journaling 7% 29% 21% 43% 0% Online text- or SMS-based qual 8% 24% 24% 40% 4% Telephone qual 11% 20% 15% 52% 3% n (range) = 104-133 Takeaway: Among brand-side researchers, the focus group and IDI methods with the most potential is AI- or chatbot-moderated qual (only 48% of probable users are current users). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Online qual with webcams 68% 85% 78% 78% 73% 56% 67% +11% In-person qual 93% 81% 65% 72% 69% 70% 59% -11% Online communities for qual 73% 74% 65% 57% 56% 53% 53% -- Mobile qual 44% 35% 41% 53% 54% 43% 41% -2% Bulletin board studies 45% 48% 41% 37% 25% 24% 36% +12% Mobile diaries/journaling 65% 62% 55% 42% 31% 45% 36% -9% AI-/chatbot-moderated qual 17% 15% 20% 19% 24% 45% 33% -12% Online text- or SMS-based qual 51% 50% 46% 35% 44% 33% 32% -1% Telephone qual 57% 65% 46% 47% 32% 39% 31% -8% Average number used: 5.1 5.1 4.6 4.4 4.1 4.1 3.9 -0.2 n (range) = 298 207 182 214 190 119-146 104-133 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side researchers, online qual with webcams (67%), in-person qual (59%), and online communities for qual (53%) are perennially top-three methods; use of bulletin board studies increased from 24% to 36% while AI-/chatbot-moderated qual fell from 45% to 33% and in-person qual dropped from 70% to 59%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar AI-/chatbot-moderated qual 34% 21% 38% 7% 0% Online communities for qual 26% 42% 22% 10% 1% In-person qual 31% 42% 12% 12% 2% Online qual with webcams 30% 33% 22% 15% 0% Bulletin board studies 12% 38% 32% 14% 3% Online text- or SMS-based qual 23% 36% 23% 18% 1% Telephone qual 14% 50% 12% 24% 0% Mobile qual 22% 28% 24% 21% 5% Mobile diaries/journaling 13% 29% 23% 28% 6% n (range) = 85-105 Takeaway: Among brand-side analytics professionals, the focus group and IDI methods with the most potential are AI- or chatbot-moderated qual (only 59% of probable users are current users) and bulletin board studies (61%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A In-person qual 73% 68% 64% 73% +9% Online communities for qual 52% 64% 61% 67% +6% Telephone qual 54% 50% 50% 64% +14% Online qual with webcams 64% 46% 49% 63% +14% Online text- or SMS-based qual 52% 56% 48% 59% +11% AI-/chatbot-moderated qual 44% 50% 64% 55% -9% Mobile qual 52% 54% 47% 50% +3% Bulletin board studies 36% 28% 46% 50% +4% Mobile diaries/journaling 32% 37% 40% 42% +2% Average number used: 4.6 4.5 4.7 5.2 +0.5 n (range) = 182 194 99-116 85-105 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side analytics professionals, in-person qual (73%) and online communities for qual (67%) have been top-three methods for each of the past three years; use of online qual with webcams increased from 49% to 63% and telephone qual grew from 50% to 64%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics Online qual with webcams 44% 48% In-person qual 42% 42% Mobile qual 41% 44% Online communities for qual 39% 38% Telephone qual 35% 22% AI-/chatbot-moderated qual 30% 62% Online text- or SMS-based qual 25% 40% Mobile diaries/journaling 20% 32% Bulletin board studies 14% 25% n (range) = 104-133 85-105 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side analytics professionals who use AI-/chatbot-moderated qual use it regularly (62%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online qual with webcams 39% 69% 74% 74% 81% In-person qual 39% 62% 60% 73% 74% Online communities for qual 45% 45% 55% 70% 72% Mobile diaries/journaling 35% 33% 44% 68% 63% Mobile qual 41% 46% 52% 61% 63% AI-/chatbot-moderated qual 38% 11% 45% 35% 61% Bulletin board studies 31% 37% 51% 73% 56% Telephone qual 25% 35% 48% 52% 43% Online text- or SMS-based qual 17% 26% 30% 29% 43% Average number used: 3.1 3.6 4.6 5.3 5.6 n (range) = 20-27 88-109 46-56 33-39 30-45 Green shading indicates top three most-used methodologies. Takeaway: Online qual with webcams is among the top three most-used in each supplier segment; in-person qual also in the top three for all segments but tech-led suppliers (39%). Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Online qual with webcams 61% 76% 77% 68% 59% Online communities for qual 57% 27% 50% 66% 57% In-person qual 34% 56% 61% 69% 53% Bulletin board studies 31% 38% 33% 48% 51% Mobile diaries/journaling 61% 31% 38% 28% 46% Telephone qual 25% 41% 55% 18% 44% Mobile qual 33% 33% 70% 52% 42% AI-/chatbot-moderated qual 37% 36% 42% 30% 40% Online text- or SMS-based qual 59% 23% 42% 32% 34% n (range) = 20-27 88-109 46-56 33-39 30-45 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: In each supplier segment, most users of online qual with webcams use them regularly; the same is true in four segments each for online communities for qual and in-person qual. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online communities for qual 26% 19% 22% 33% 0% Online qual with webcams 23% 15% 18% 44% 0% Mobile qual 14% 28% 15% 44% 0% Mobile diaries/journaling 22% 14% 21% 44% 0% AI-/chatbot-moderated qual 14% 24% 14% 48% 0% In-person qual 13% 26% 4% 58% 0% Bulletin board studies 9% 21% 10% 51% 9% Telephone qual 6% 18% 13% 62% 0% Online text- or SMS-based qual 10% 7% 6% 77% 0% n (range) = 20-27 Takeaway: Among tech-led suppliers, the focus group and IDI methods with the most potential are mobile diaries/journaling (only 63% who will probably use it currently do), followed by telephone qual (65%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Online communities for qual 81% 71% 27% 44% 39% 33% 45% +12% Mobile qual 44% 48% 48% 50% 34% 40% 41% +1% Online qual with webcams 69% 71% 22% 57% 52% 52% 39% -13% In-person qual 50% 40% 26% 32% 38% 21% 39% +18% AI-/chatbot-moderated qual 14% 28% 40% 21% 26% 38% 38% -- Mobile diaries/journaling 74% 71% 3.4 54% 32% 28% 35% +7% Bulletin board studies 67% 49% 27% 31% 32% 23% 31% +8% Telephone qual 50% 31% 48% 31% 30% 23% 25% +2% Online text- or SMS-based qual 61% 54% 22% 41% 39% 23% 17% -6% Average number used 5.1 4.6 3.4 3.6 3.2 2.8 3.1 +0.3 n (range) = 54-97 35-50 122-125 70 30-43 28-40 20-27 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among tech-led suppliers, online qual with webcams (45%) has been among the three most-used for the last four years, mobile qual (41%) has been for the past two; use of in-person qual increased from 21% to 39% while online qual with webcams fell from 52% to 39%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar In-person qual 39% 35% 14% 7% 5% AI-/chatbot-moderated qual 24% 37% 27% 12% 0% Online qual with webcams 48% 34% 4% 12% 3% Mobile qual 27% 36% 15% 19% 3% Online communities for qual 41% 31% 4% 22% 2% Mobile diaries/journaling 29% 34% 10% 25% 2% Bulletin board studies 29% 28% 14% 28% 2% Online text- or SMS-based qual 14% 28% 26% 27% 4% Telephone qual 19% 24% 5% 44% 8% n (range) = 30-45 Takeaway: Among service-led suppliers with 500+ FTE, the focus group and IDI method with the most potential is online text- or SMS-based qual (only 62% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Online qual with webcams 79% 72% 71% 72% 79% 78% 81% +3% In-person qual 92% 72% 60% 67% 74% 79% 74% -5% Online communities for qual 81% 79% 72% 66% 77% 79% 72% -7% Mobile diaries/journaling 82% 70% 64% 52% 68% 72% 63% -9% Mobile qual 44% 54% 44% 54% 76% 68% 63% -5% AI-/chatbot-moderated qual 27% 22% 21% 26% 30% 47% 61% +14% Bulletin board studies 65% 52% 50% 52% 60% 51% 56% +5% Telephone qual 79% 62% 56% 57% 69% 42% 43% +1% Online text- or SMS-based qual 73% 69% 53% 41% 45% 61% 43% -18% Average number used: 6.2 5.5 4.9 4.9 5.8 5.8 5.6 -- n (range) = 84-106 71-85 117-129 97 60-74 51-72 30-45 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 500+ FTE, online communities for qual (72%) is a perennial top three most-used method and online qual with webcams (81%) has been in the top three for six straight years; use AI-/chatbot-moderated qual increased from 47% to 61% while online text- or SMS-based qual fell from 61% to 43%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online qual with webcams 50% 24% 15% 11% 0% Online communities for qual 46% 24% 13% 17% 0% Bulletin board studies 35% 38% 10% 17% 0% In-person qual 51% 22% 2% 25% 0% Mobile diaries/journaling 19% 49% 6% 23% 2% Mobile qual 32% 29% 13% 19% 7% AI-/chatbot-moderated qual 11% 25% 37% 28% 0% Online text- or SMS-based qual 9% 19% 29% 39% 3% Telephone qual 9% 43% 5% 41% 2% n (range) = 33-39 Takeaway: Among service-led suppliers with 101-500 FTE, the focus group and IDI methods with the most potential are AI- or chatbot-moderated qualitative interviews or groups (only 49% who will probably use it currently do) and online text- or SMS-based qual (also 49%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online qual with webcams 89% 88% 70% 83% 71% 85% 74% -11% Bulletin board studies 73% 67% 57% 63% 59% 55% 73% +18% In-person qual 95% 84% 61% 79% 70% 69% 73% +4% Online communities for qual 88% 76% 69% 71% 63% 54% 70% +16% Mobile diaries/journaling 85% 78% 62% 70% 54% 54% 68% +14% Mobile qual 66% 56% 62% 67% 66% 56% 61% +5% Telephone qual 83% 74% 55% 67% 51% 60% 52% -8% AI-/chatbot-moderated qual 19% 15% 18% 48% 26% 30% 35% +5% Online text- or SMS-based qual 73% 70% 45% 12% 42% 39% 29% -10% Average number used: 6.7 6.1 5.0 5.6 5.0 5.0 5.3 +0.3 n (range) = 99-108 76-89 127-134 102 60-75 48-59 33-39 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 101-500 FTE, online qual with webcams (74%) is perennially a top-three method, and in-person qual (73%) has been in the top three every year but one; use of bulletin board studies increased from 55% to 73%; online communities for qual, 54% to 70%; and mobile diaries/journaling, 54% to 68%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online qual with webcams 56% 17% 14% 12% 0% Online communities for qual 28% 27% 22% 23% 0% In-person qual 37% 23% 17% 24% 0% Mobile qual 36% 15% 21% 28% 0% AI-/chatbot-moderated qual 19% 26% 25% 27% 3% Bulletin board studies 17% 34% 18% 30% 1% Mobile diaries/journaling 17% 27% 21% 28% 6% Telephone qual 26% 22% 14% 38% 0% Online text- or SMS-based qual 12% 17% 31% 35% 5% n (range) = 46-56 Takeaway: Among service-led suppliers with 21-100 FTE, the focus group and IDI method with the most potential is online text- or SMS-based qual (only 49% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Online qual with webcams 68% 86% 78% 82% 78% 70% 74% +4% In-person qual 93% 74% 70% 76% 72% 55% 60% +5% Online communities for qual 69% 70% 69% 68% 63% 57% 55% -2% Mobile qual 50% 62% 56% 71% 68% 59% 52% -7% Bulletin board studies 56% 56% 49% 51% 47% 53% 51% -2% Telephone qual 77% 72% 58% 66% 64% 40% 48% +8% AI-/chatbot-moderated qual 14% 14% 19% 42% 26% 25% 45% +20% Mobile diaries/journaling 78% 73% 70% 61% 63% 47% 44% -3% Online text- or SMS-based qual 49% 48% 51% 41% 54% 46% 30% -16% Average number used: 5.5 5.6 5.2 5.6 5.3 4.5 4.6 +0.1 n (range) = 150-169 112-130 142-145 183 93-108 75-91 46-56 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 21-100 FTE, online qual with webcams (74%) has been among the top three most-used methods for six years, and in-person qual (60%) has been in the top three every year but one; use of AI-/chatbot-moderated qual rose from 25% to 45% while online text- or SMS-based qual fell from 46% to 30%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Online qual with webcams 53% 16% 13% 18% 0% In-person qual 35% 28% 17% 19% 2% Mobile qual 15% 31% 26% 26% 2% Mobile diaries/journaling 10% 23% 28% 30% 8% Bulletin board studies 14% 23% 20% 39% 4% Online communities for qual 12% 33% 11% 40% 4% Telephone qual 14% 21% 9% 55% 1% Online text- or SMS-based qual 6% 20% 16% 52% 6% AI-/chatbot-moderated qual 4% 7% 26% 57% 6% n (range) = 88-109 Takeaway: Among service-led suppliers with ≤20 FTE, the focus group and IDI method with the most potential is AI- or chatbot-moderated qual (only 30% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Online qual with webcams 70% 84% 74% 83% 72% 65% 69% +4% In-person qual 96% 84% 69% 81% 66% 64% 62% -2% Mobile qual 43% 39% 41% 63% 48% 49% 46% -2% Online communities for qual 59% 63% 55% 60% 50% 47% 45% -9% Bulletin board studies 49% 58% 49% 46% 35% 40% 37% -3% Telephone qual 82% 69% 59% 65% 50% 40% 35% +4% Mobile diaries/journaling 66% 65% 56% 52% 39% 42% 33% -3% Online text- or SMS-based qual 43% 50% 33% 34% 32% 30% 26% -5% AI-/chatbot-moderated qual 4% 6% 7% 9% 3% 10% 11% +1% Average number used: 5.1 5.2 4.4 4.9 3.9 3.9 3.6 -0.3 n (range) = 270-310 185-221 234-239 271 114-133 135-154 88-109 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with ≤20 FTE, online qual with webcams (69%) and in-person qual (62%) are perennially among the three most-used methods, and mobile qual (46%) has been for the past two years. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC Interpretation] Average qualitative-method portfolios are contracting across most segments — tech-led suppliers from 5.1 to 3.1 methods since first tracked, brand-side researchers from 5.1 to 3.9 — but this reflects consolidation into fewer methods rather than a decline in qual overall. Brand-side analytics is the exception, growing its portfolio. Three methods remain structurally durable and high-intensity: online qual with webcams, in-person qual, and online communities for qual. The emerging method is AI-/chatbot-moderated qual, up at least +10% in every segment since 20A, though it slipped about −10% in both brand segments this year even as most supplier segments held or rose. Its saturation is consistently low (48% among brand researchers, 30%–49% among several supplier segments), making it the most consistent near-term adoption opportunity in the family. Meanwhile online text-/SMS-based qual fell by double digits in five segments; its decline alongside AI-moderated growth is suggestive of substitution rather than simple contraction, though the data cannot confirm it. Brand-side analytics shows the highest intensity for AI-moderated qual and adopts quickly once a method is on its radar, and may be a leading indicator of where qual is heading. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Sample In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across seven methods related to sample. WHICH SAMPLING METHODS ARE RISING? [ORIENTATION] THREE MOST-USED METHODS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Proprietary panels from external supplier 67% 55% 71% 73% 86% 88% 87% Proprietary panels you own 49% 52% 24% 17% 58% 56% 64% Social media recruiting 30% 63% 30% 32% 42% 40% 52% Tools to detect sample fraud from supplier 27% 52% 61% 57% 74% 73% 76% In-house tools to detect sample fraud 24% 53% 68% 45% 73% 85% 81% Programmatic sampling 23% 54% 47% 21% 50% 34% 54% Average number of methodologies used: 2.4 3.6 3.3 2.6 4.1 4.1 4.6 n = 176 152 39 158 79 56 55 Green shading indicates top three most-used methodologies. Takeaway: Proprietary panels from an external supplier are the most-used sample method in each segment, and tools to detect sample fraud from a supplier and in-house tools to detect sample fraud are among the top three in each supplier segment; social media recruiting is in the top three in each brand-side segment. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Proprietary panels you own +10% 0% -3% -8% +13% +1% -3% River or web-intercept sampling +5% +4% -7% -4% -4% +7% -7% In-house tools to detect sample fraud +4% -2% -4% -4% +5% +16% -4% Programmatic sampling +2% +1% +9% -7% +14% -8% +9% Social media recruiting +1% -3% +5% -5% -10% +15% +5% Proprietary panels from external supplier 0% +4% +2% +3% +8% +6% +2% Tools to detect sample fraud from supplier -10% +4% +4% +13% +9% +3% +4% Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: Programmatic sampling and social media recruiting increased at least +5% in three segments each; proprietary panels they own increased at least +10% in brand-side research and service-led suppliers with 21-100 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 SAMPLE METHODS 2026 Method 2025 Precedent 2025 Family Programmatic sampling Programmatic sampling Sample Social media recruiting Social media recruiting Sample River or web-intercept sampling River or web-intercept sampling Sample Proprietary panels from external supplier Proprietary panels from external supplier Sample Proprietary panels you own Proprietary panels you own Sample Tools to detect sample fraud from supplier Tools to detect sample fraud from supplier Sample In-house tools to detect sample fraud In-house tools to detect sample fraud Sample Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT Research Analytics Research – analytics Proprietary panels from external supplier 67% 55% +12% Proprietary panels you own 49% 52% -3% Social media recruiting 30% 63% -33% Tools to detect sample fraud from supplier 27% 52% -25% In-house tools to detect sample fraud 24% 53% -29% Programmatic sampling 23% 54% -31% River or web-intercept sampling 22% 36% -14% Average number of sample methodologies used: 2.4 3.6 -1.2 n = 176 152 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more sample methods than researchers on average (3.6 to 2.4), with the largest gaps in social media recruiting (63% to 30%), programmatic sampling (54% to 23%), in-house tools to detect sample fraud (53% to 24%), and tools to detect sample fraud from suppliers (52% to 27%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Proprietary panels from external supplier 38% 28% 14% 15% 4% Proprietary panels you own 33% 16% 13% 33% 6% Social media recruiting 10% 20% 29% 36% 5% Tools to detect sample fraud from supplier 16% 11% 29% 31% 12% In-house tools to detect sample fraud 12% 12% 20% 46% 10% Programmatic sampling 9% 13% 20% 31% 26% River or web-intercept sampling 8% 14% 16% 31% 31% n = 176 Takeaway: Among brand-side researchers, the sample methods with the most potential are tools to detect sample fraud from supplier (only 48% of probable users currently do), social media recruiting (51%), and programmatic sampling (53%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A – 25A Proprietary panels 68% 68% 63% 79% -- -- -- -- Proprietary panels from external supplier -- -- -- 70% 69% 67% 67% -- Proprietary panels you own -- -- -- 44% 47% 39% 49% +10% Alternatives to panel samples -- 29% 23% 53% -- -- -- -- Social media recruiting -- -- -- 39% 35% 28% 30% +2% River or web-intercept sampling -- -- -- 17% 20% 17% 22% +5% Programmatic sampling -- -- -- 22% 19% 21% 23% +2% Tools to detect sample fraud -- -- -- 42% -- -- -- -- Tools to detect sample fraud from supplier -- -- -- 34% 40% 37% 27% -10% In-house tools to detect sample fraud -- -- -- 26% 26% 21% 24% +3% Average number used: 0.7 1.0 0.9 2.5 2.7 2.4 2.4 -- n (range) = 298 207 182-188 214 108-122 107-129 176 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among brand-side researchers, proprietary panels from an external supplier (67%) and proprietary panels they own (49%) have been among the three most-used methods since 23A; use of proprietary panels they own increased from 39% to 49% while use of tools to detect sample fraud from a supplier fell from 37% to 27%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Programmatic sampling 16% 38% 31% 7% 9% Social media recruiting 23% 41% 21% 13% 3% Proprietary panels from external supplier 18% 37% 27% 14% 4% Tools to detect sample fraud from supplier 26% 26% 27% 17% 4% In-house tools to detect sample fraud 33% 20% 25% 16% 6% Proprietary panels you own 24% 28% 25% 19% 5% River or web-intercept sampling 9% 27% 30% 15% 19% n (range) = 152 Takeaway: Among brand-side analytics professionals, the sample method with the most potential is river or web-intercept sampling (only 54% of probable users currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Alternatives to panel samples 77% -- -- -- -- Social media recruiting 58% 49% 66% 63% -3% Programmatic sampling 50% 47% 53% 54% +1% River or web-intercept sampling 26% 23% 32% 36% +4% Proprietary panels 68% -- -- -- -- Proprietary panels from external supplier 54% 47% 51% 55% +4% Proprietary panels you own 42% 51% 51% 52% +1% Tools to detect sample fraud 52% -- -- -- -- In-house tools to detect sample fraud 43% 41% 55% 53% -2% Tools to detect sample fraud from supplier 42% 50% 48% 52% +4% Average number used: 3.2 3.1 3.6 3.6 -- n (range) = 182 109-124 90-120 152 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among brand-side analytics professionals, social media recruiting (63%) is a perennial top three most-used method, and programmatic sampling (54%) has been in the top three for three of four years. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics Proprietary panels you own 68% 46% Tools to detect sample fraud from supplier 59% 51% Proprietary panels from external supplier 57% 32% In-house tools to detect sample fraud 49% 62% Programmatic sampling 42% 29% River or web-intercept sampling 37% 24% Social media recruiting 32% 36% n = 176 152 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side researchers who use proprietary panels they own (68%), tools to detect sample fraud from a supplier (59%), and proprietary panels from an external supplier (57%) use them regularly; among brand-side analytics professionals, most users of in-house tools to detect sample fraud (62%) and supplier tools to detect fraud use them regularly (51%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Proprietary panels from external supplier 71% 73% 86% 88% 87% In-house tools to detect sample fraud 68% 45% 73% 85% 81% Tools to detect sample fraud from supplier 61% 57% 74% 73% 76% Proprietary panels you own 24% 17% 58% 56% 64% Programmatic sampling 47% 21% 50% 34% 54% Social media recruiting 30% 32% 42% 40% 52% River or web-intercept sampling 29% 19% 31% 29% 49% Average number used: 3.3 2.6 4.1 4.1 4.6 n (range) = 39 158 79 56 55 Green shading indicates top three most-used methodologies. Takeaway: In each supplier segment, the top three most-used methods are proprietary panels from an external supplier, in-house tools to detect sample fraud, and tools to detect sample fraud from a supplier. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE In-house tools to detect sample fraud 84% 75% 80% 84% 79% Proprietary panels you own 93% 57% 84% 88% 69% Proprietary panels from external supplier 69% 67% 64% 79% 68% Tools to detect sample fraud from supplier 78% 73% 72% 88% 68% Programmatic sampling 52% 27% 47% 54% 51% Social media recruiting 38% 24% 30% 48% 40% River or web-intercept sampling 50% 18% 44% 33% 30% n (range) = 39 158 79 56 55 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: In each supplier segment, most users of in-house tools to detect sample fraud, proprietary panels they own, proprietary panels from an external supplier, and tools to detect sample fraud from a supplier use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Proprietary panels from external supplier 50% 22% 13% 16% 0% In-house tools to detect sample fraud 57% 11% 11% 17% 4% Tools to detect sample fraud from supplier 48% 13% 16% 19% 4% Programmatic sampling 25% 22% 8% 35% 10% River or web-intercept sampling 14% 14% 19% 43% 10% Social media recruiting 11% 18% 14% 53% 3% Proprietary panels you own 23% 2% 12% 58% 6% n = 39 Takeaway: Among tech-led suppliers, the sample method with the most potential is river or web-intercept sampling (only 60% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Proprietary panels 68% 65% 64% 81% -- -- -- -- Proprietary panels from external supplier -- -- -- 76% 76% 69% 71% +2% Proprietary panels you own -- -- -- 39% 56% 27% 24% -3% Tools to detect sample fraud -- -- -- 67% -- -- -- -- In-house tools to detect sample fraud -- -- -- 56% 65% 73% 68% -5% Tools to detect sample fraud from supplier -- -- -- 60% 55% 57% 61% +4% Alternatives to panel samples -- 26% 22% 79% -- -- -- -- Programmatic sampling -- -- -- 55% 45% 38% 47% +9% Social media recruiting -- -- -- 48% 31% 25% 30% +5% River or web-intercept sampling -- -- -- 49% 37% 36% 29% -7% Average number used: 0.7 0.9 0.9 3.8 3.6 3.3 3.3 -- n (range) = 90 46-50 122-125 70 28-42 29-34 39 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among tech-led suppliers, proprietary panels from an external supplier (71%) and in-house tools to detect sample fraud (68%) are perennially among the three most-used methods, and tools to detect sample fraud from supplier (61%) has been in the top three for three of the past four years. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Tools to detect sample fraud from supplier 52% 25% 15% 5% 4% Proprietary panels from external supplier 59% 28% 2% 5% 6% In-house tools to detect sample fraud 64% 17% 7% 8% 5% Proprietary panels you own 44% 20% 12% 17% 7% River or web-intercept sampling 15% 35% 23% 14% 13% Social media recruiting 21% 31% 15% 23% 9% Programmatic sampling 27% 26% 13% 7% 27% n = 55 Takeaway: Among service-led suppliers with 500+ FTE, the sample method with the most potential is river or web-intercept sampling (only 68% who will probably use it currently do); each other method is at least 78% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Proprietary panels 86% 88% 84% 92% -- -- -- -- Proprietary panels from external supplier -- -- -- 84% 79% 91% 87% -4% Proprietary panels you own -- -- -- 73% 65% 64% 64% -- Tools to detect sample fraud -- -- -- 84% -- -- -- -- In-house tools to detect sample fraud -- -- -- 78% 69% 68% 81% +13% Tools to detect sample fraud from supplier -- -- -- 73% 75% 82% 76% -6% Alternatives to panel samples -- 40% 44% 76% -- -- -- -- Programmatic sampling -- -- -- 55% 61% 65% 54% -11% Social media recruiting -- -- -- 56% 46% 56% 52% -4% River or web-intercept sampling -- -- -- 59% 44% 43% 49% +6% Average number used: 0.9 1.3 1.3 4.8 4.4 4.7 4.6 -0.1 n (range) = 104 85-88 117-129 97 56-65 52-61 55 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 500+ FTE, proprietary panels from an external supplier (87%), in-house tools to detect sample fraud (81%), and tools to detect sample fraud from a supplier (76%) are perennially the three most-used methods; use of in-house tools to detect sample fraud increased from 68% to 81% and use of programmatic sampling fell from 65% to 54%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Proprietary panels from external supplier 69% 19% 4% 1% 7% In-house tools to detect sample fraud 71% 14% 4% 7% 4% Tools to detect sample fraud from supplier 64% 9% 7% 12% 8% Social media recruiting 19% 21% 26% 27% 7% Proprietary panels you own 50% 7% 5% 33% 6% Programmatic sampling 19% 16% 17% 10% 39% River or web-intercept sampling 10% 20% 9% 27% 34% n = 56 Takeaway: Among service-led suppliers with 101-500 FTE, the sample method with the most potential is social media recruiting (only 61% who will probably use it currently do); each other method is at least 76% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Proprietary panels 78% 78% 76% 93% -- -- -- -- Proprietary panels from external supplier -- -- -- 86% 70% 81% 88% +7% Proprietary panels you own -- -- -- 50% 51% 55% 56% +1% Tools to detect sample fraud -- -- -- 87% -- -- -- -- In-house tools to detect sample fraud -- -- -- 81% 71% 69% 85% +16% Tools to detect sample fraud from supplier -- -- -- 74% 66% 69% 73% +4% Alternatives to panel samples -- 37% 32% 74% -- -- -- -- Social media recruiting -- -- -- 58% 45% 25% 40% +15% Programmatic sampling -- -- -- 51% 41% 42% 34% -8% River or web-intercept sampling -- -- -- 40% 32% 22% 29% +7% Average number used: 0.8 1.1 1.1 4.4 3.8 3.6 4.1 +0.5 n (range) = 108 81-89 127-134 102 58-72 49-62 56 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 101-500 FTE, proprietary panels from an external supplier (88%), in-house tools to detect sample fraud (85%), and tools to detect sample fraud from a supplier (73%) are perennially the three most-used methods; use of in-house tools to detect sample fraud increased from 69% to 85%, and social media recruiting increased from 25% to 40%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Proprietary panels from external supplier 55% 31% 3% 9% 3% Tools to detect sample fraud from supplier 53% 20% 9% 5% 12% In-house tools to detect sample fraud 58% 14% 9% 7% 12% Programmatic sampling 23% 26% 16% 13% 21% Social media recruiting 13% 30% 23% 27% 8% Proprietary panels you own 49% 9% 8% 32% 3% River or web-intercept sampling 13% 17% 14% 34% 22% n = 79 Takeaway: Among service-led suppliers with 21-100 FTE, the sample method with the most potential is social media recruiting (only 65% who will probably use it currently do); each other method is at least 69% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Proprietary panels 67% 80% 77% 89% -- -- -- -- Proprietary panels from external supplier -- -- -- 79% 76% 78% 86% +8% Proprietary panels you own -- -- -- 55% 51% 44% 58% +14% Tools to detect sample fraud -- -- -- 73% -- -- -- -- Tools to detect sample fraud from supplier -- -- -- 56% 59% 65% 74% +9% In-house tools to detect sample fraud -- -- -- 65% 73% 68% 73% +5% Alternatives to panel samples -- 33% 38% 73% -- -- -- -- Programmatic sampling -- -- -- 36% 45% 35% 50% +15% Social media recruiting -- -- -- 55% 54% 52% 42% -10% River or web-intercept sampling -- -- -- 36% 28% 34% 31% -3% Average number used: 0.7 1.1 1.1 3.8 3.9 3.8 4.1 +0.3 n (range) = 163 122-130 142-145 184 82-104 79-84 79 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 21-100 FTE, proprietary panels from an external supplier (86%), in-house tools to detect sample fraud (73%), and tools to detect sample fraud from a supplier (74%) are perennially the three most-used methods; use of social media recruiting increased from 35% to 50%, proprietary panels they own increased from 44% to 58%, and social media recruiting decreased from 52% to 42%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Proprietary panels from external supplier 49% 24% 11% 11% 4% Tools to detect sample fraud from supplier 42% 15% 17% 16% 9% In-house tools to detect sample fraud 34% 11% 24% 26% 6% Social media recruiting 8% 24% 25% 41% 3% Programmatic sampling 6% 15% 22% 30% 27% River or web-intercept sampling 3% 15% 18% 38% 25% Proprietary panels you own 10% 7% 14% 65% 5% n = 159 Takeaway: Among service-led suppliers with ≤20 FTE, the sample methods with the most potential are programmatic sampling (only 49% who will probably use it currently do), river or web-intercept sampling (51%), social media recruiting (56%) and proprietary panels they own (56%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Proprietary panels 67% 74% 64% 78% -- -- -- -- Proprietary panels from external supplier -- -- -- 73% 67% 70% 73% +3% Proprietary panels you own -- -- -- 29% 23% 25% 17% -8% Tools to detect sample fraud -- -- -- 63% -- -- -- -- Tools to detect sample fraud from supplier -- -- -- 48% 45% 45% 57% +12% In-house tools to detect sample fraud -- -- -- 51% 42% 49% 45% -4% Alternatives to panel samples -- 25% 22% 70% -- -- -- -- Social media recruiting -- -- -- 56% 44% 36% 32% -4% Programmatic sampling -- -- -- 27% 31% 28% 21% -7% River or web-intercept sampling -- -- -- 23% 21% 22% 19% -3% Average number used: 0.7 1.0 0.9 3.1 2.7 2.8 2.6 -0.2 n (range) = 267 194-221 234-239 271 110-138 124-149 158 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with ≤20 FTE, proprietary panels from an external supplier (73%) is perennially the most-used method, tools to detect sample fraud from supplier (57%) have been in the top three for the last three years, and in-house tools to detect sample fraud (45%) have been in the top three for three of four years; use of tools to detect sample fraud from supplier increased from 45% to 57%. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC Interpretation] GRIT’s seven sample methods separate into two tiers. Proprietary panels and fraud-detection tools — both supplier-provided and in-house — dominate usage in nearly every segment and function as embedded infrastructure, with fraud-tool intensity running 70–88%. “Alternative” methods (programmatic sampling, social-media recruiting, river/web-intercept) sit in a consistently lower tier, especially among brand-side researchers and smaller suppliers. Fraud detection is the most dynamic story: in-house tools rose by double digits among service-led suppliers with 101–500 and 500+ FTE, and the cross-segment momentum suggests ongoing sample-quality concern is actively driving investment. Tech-led suppliers appear to enable and verify access — heavy fraud-tool use, external panel relationships — rather than own sample assets themselves; their use of owned panels is less than half that of larger service-led suppliers. Interest in owned panels may be growing elsewhere: proprietary panels rose +10% to 49% among brand researchers and +14% to 58% among 21–100 FTE suppliers, possibly reflecting a move toward directly controlled sample. Analytics professionals use far more sample methods than researchers (3.6 versus 2.4 on average) and are markedly heavier users of fraud detection, consistent with quality verification embedded in ongoing data workflows rather than handled project by project. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Observational Research In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across six observational research methods. ARE OBSERVATIONAL METHODS GOING MAINSTREAM? [ORIENTATION] THREE MOST-USED METHODS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Passive metering 31% 56% 18% 11% 16% 21% 55% In-store/shopping observations 24% 53% 25% 39% 39% 46% 48% Ethnography (NOT mobile) 23% 35% 23% 44% 44% 59% 74% Mobile ethnography 22% 48% 26% 31% 59% 64% 52% Automated measures/people meters 21% 64% 6% 11% 12% 30% 34% Average number used: 1.4 2.9 1.1 1.4 1.9 2.4 2.9 n (range) = 107-129 96-105 21-26 91-108 45-61 31-41 30-35 Green shading indicates top three most-used methodologies. Takeaway: In-store/shopping observations are a top three most-used observational method in each segment except service-led suppliers with 500+ FTE; non-mobile ethnography is top-three in each segment except brand-side analytics; and mobile ethnography is top-three in each supplier segment. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Wearables +9% +13% -2% -1% +1% +1% -1% Automated measures/people meters +6% +8% -15% -1% +2% +20% -4% In-store/shopping observations -7% +17% -2% -9% +1% +5% -10% Mobile ethnography -10% +19% -4% -4% +17% +19% -7% Ethnography (NOT mobile) -15% +9% -4% -1% +7% +20% +20% n (range) = 107-129 96-105 21-26 91-108 45-61 31-41 30-35 Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: Mobile ethnography increased by at least +10% in three segments while non-mobile increased over +5% in four. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 OBSERVATIONAL METHODS 2026 Method 2025 Precedent 2025 Family Automated measures/people meters Automated measures/people meters Observational Ethnography (NOT mobile) Ethnography (NOT mobile) Observational In-store/shopping observations In-store/shopping observations Observational Mobile ethnography Mobile ethnography Observational Passive metering (sensors, usage data, telemetry, IoT) Sensor/usage/telemetry + Internet of Things (IoT) (merged) Observational Wearables Wearables Observational Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT Research Analytics Research – analytics Passive metering 31% 56% -25% In-store/shopping observations 24% 53% -29% Ethnography (NOT mobile) 23% 35% -12% Mobile ethnography 22% 48% -26% Automated measures/people meters 21% 64% -43% Wearables 15% 31% -16% Average number used 1.4 2.9 -1.5 n (range) = 107-129 96-105 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more observational methods than researchers on average (2.9 to 1.4), with the largest gaps in automated measures/people meters (64% to 21%), in-store/shopping observations (53% to 24%), mobile ethnography (48% to 22%), and passive metering (56% to 31%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Ethnography (NOT mobile) 6% 16% 28% 44% 5% Mobile ethnography 7% 15% 28% 41% 9% Passive metering 15% 16% 18% 41% 10% In-store/shopping observations 12% 12% 17% 56% 3% Automated measures/people meters 8% 13% 15% 47% 17% Wearables 2% 12% 16% 66% 4% n (range) = 107-129 Takeaway: Among brand-side researchers, the observational methods with the most potential are mobile ethnography (only 43% of probable users currently do), non-mobile ethnography (44%), and wearables (48%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A – 25A Passive metering 14% 13% 14% 28% -- -- 31% -- Sensor/usage/telemetry -- -- -- 12% 18% 12% -- -- Internet of Things (IoT) -- -- -- 16% 19% 9% -- -- Wearables -- -- -- 13% 12% 6% 15% +9% Ethnography (NOT mobile) -- -- -- 44% 39% 37% 23% -14% In-store/shopping observations 47% 45% 38% 38% 31% 32% 24% -8% Mobile ethnography 36% 29% 31% 34% 32% 31% 22% -9% Automated measures/people meters 21% 24% 21% 12% 20% 15% 21% +6% Average number used: 1.2 1.1 1.0 1.7 1.7 1.4 1.4 -- n = (range) 298 209 182 214 113-135 122-141 107-129 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among brand-side researchers, non-mobile ethnography (23%) and in-store/shopping observations (24%) have been top three most-used methods each year; use of non-mobile ethnography fell from 37% to 23%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Automated measures/people meters 23% 41% 19% 15% 2% Passive metering 28% 27% 20% 24% 1% Mobile ethnography 9% 38% 26% 20% 6% In-store/shopping observations 19% 34% 18% 29% 0% Ethnography (NOT mobile) 10% 25% 23% 32% 10% Wearables 10% 21% 26% 41% 1% n (range) = 96-105 Takeaway: Among brand-side analytics professionals, the observational method with the most potential is wearables (only 54% of probable users currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Automated measures/people meters 42% 53% 56% 64% +8% Passive metering 48% -- -- 56% -- Internet of Things (IoT) 39% 51% 48% -- -- Sensor/usage/telemetry 29% 42% 45% -- -- Wearables 20% 24% 19% 31% +12% In-store/shopping observations 38% 53% 36% 53% +17% Mobile ethnography 27% 30% 28% 48% +20% Ethnography (NOT mobile) 25% 32% 27% 35% +8% Average number used: 2.2 2.9 2.6 2.9 +0.3 n = (range) 182 114-132 99-129 96-105 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among brand-side analytics professionals, automated measures/people meters (64%) is a perennial top three most-used method, as are different versions of passive metering (56%); use of mobile ethnography increased from 28% to 48%; in-store/shopping observations, from 36% to 53%; and wearables from 19% to 31%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics In-store/shopping observations 49% 37% Passive metering (sensors, usage data, telemetry, IoT) 48% 51% Automated measures/people meters 40% 36% Mobile ethnography 31% 20% Ethnography (NOT mobile) 28% 29% Wearables 16% 32% n (range) = 107-129 96-105 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side analytics professionals who use passive metering use it regularly (51%), as do nearly half of researchers (48%); nearly half of researchers who use in-store/shopping observations (49%) use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Ethnography (NOT mobile) 23% 44% 44% 59% 74% Passive metering 18% 11% 16% 21% 55% Mobile ethnography 26% 31% 59% 64% 52% In-store/shopping observations 25% 39% 39% 46% 48% Automated measures/people meters 6% 11% 12% 30% 34% Wearables 12% 6% 15% 16% 23% Average number used: 1.1 1.4 1.9 2.4 2.9 n = (range) 21-26 91-108 45-61 31-41 30-35 Green shading indicates top three most-used methodologies. Takeaway: In each supplier segment, mobile and non-mobile ethnography are among the top three most-used observational methods; passive metering (55%) is in the top three for service-led suppliers with 500+ FTE, and in-store/shopping observations is in the top three in each other segment. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Automated measures/people meters 100% 15% 59% 13% 58% Wearables 21% 29% 39% 0% 47% Passive metering 0% 18% 26% 0% 39% In-store/shopping observations 63% 34% 43% 23% 34% Ethnography (NOT mobile) 0% 28% 24% 23% 33% Mobile ethnography 55% 32% 36% 41% 33% n = (range) 21-26 91-108 45-61 31-41 30-35 Intensity = regular use / total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most users of automated measures/people meters among tech-led suppliers (100%) and service-led suppliers with 21-100 FTE (59%) and 500+ FTE (58%) use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Mobile ethnography 14% 12% 15% 51% 8% Passive metering 0% 18% 20% 58% 4% Wearables 3% 10% 21% 67% 0% In-store/shopping observations 16% 9% 6% 68% 0% Automated measures/people meters 6% 0% 23% 48% 23% Ethnography (NOT mobile) 0% 23% 5% 65% 6% n (range) = 21-26 Takeaway: Among tech-led suppliers, the observational methods with the most potential are automated measures/people meters (only 21% who will probably use it currently do), wearables (37%), and passive metering (47%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Mobile ethnography 37% 28% 23% 39% 14% 30% 26% -4% In-store/shopping observations 65% 43% 24% 33% 20% 28% 25% -2% Ethnography (NOT mobile) -- -- -- 30% 17% 27% 23% -4% Passive metering 18% 10% 21% 28% 9% -- 18% -- Internet of Things (IoT) -- -- -- 14% 18% 20% -- -- Sensor/usage/telemetry -- -- -- 17% 15% 14% -- -- Wearables -- -- -- 12% 5% 14% 12% -2% Automated measures/people meters 32% 26% 28% 31% 22% 21% 6% -15% Average number used: 1.5 1.1 1.0 1.7 1.1 1.5 1.1 -0.4 n = 54-97 35-50 122-125 70 35-44 28-40 21-26 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among tech-led suppliers, in-store/shopping observations (25%) is perennially among the three most-used methods; use of automated measures/people meters fell from 21% to 6%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Ethnography (NOT mobile) 24% 50% 7% 18% 2% Passive metering 22% 33% 15% 24% 5% Mobile ethnography 17% 35% 18% 28% 2% In-store/shopping observations 16% 32% 22% 27% 3% Automated measures/people meters 20% 15% 16% 35% 15% Wearables 11% 12% 16% 54% 7% n (range) = 30-35 Takeaway: Among service-led suppliers with 500+ FTE, the observational method with the most potential is wearables (only 59% who will probably use it currently do); each other method is at least 68% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Ethnography (NOT mobile) -- -- -- 53% 59% 54% 74% +20% Passive metering 48% 26% 36% 46% 42% -- 55% -- Internet of Things (IoT) -- -- -- 31% 19% 35% -- -- Sensor/usage/telemetry -- -- -- 29% 30% 30% -- -- Wearables -- -- -- 23% 18% 24% 23% -1% Mobile ethnography 47% 38% 39% 46% 47% 59% 52% -7% In-store/shopping observations 71% 55% 50% 50% 48% 58% 48% -10% Automated measures/people meters 49% 35% 43% 32% 30% 38% 34% -4% Average number used: 2.2 1.5 1.7 2.6 2.5 3.0 2.9 -0.1 n = 84-106 71-88 117-129 97 60-72 51-72 30-35 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 500+ FTE, mobile (52%) and non-mobile ethnography (74%) are perennially among the three most-used methods since 23A; use of mobile ethnography increased from 54% to 74% and use of in-store/shopping observations fell from 58% to 48%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar In-store/shopping observations 11% 35% 33% 17% 3% Mobile ethnography 26% 38% 13% 18% 5% Ethnography (NOT mobile) 13% 46% 14% 26% 2% Passive metering 0% 21% 26% 33% 21% Automated measures/people meters 4% 26% 16% 29% 25% Wearables 0% 16% 6% 56% 21% n (range) = 31-41 Takeaway: Among service-led suppliers with 101-500 FTE, the observational method with the most potential is passive metering (only 45% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Mobile ethnography 57% 47% 53% 61% 41% 45% 64% +19% Ethnography (NOT mobile) -- -- -- 60% 40% 39% 59% +20% In-store/shopping observations 74% 66% 46% 54% 54% 40% 46% +6% Automated measures/people meters 26% 21% 28% 10% 24% 10% 30% +20% Passive metering 31% 19% 25% 26% 39% -- 21% -- Internet of Things (IoT) -- -- -- 12% 26% 25% -- -- Sensor/usage/telemetry -- -- -- 15% 16% 12% -- -- Wearables -- -- -- 15% 21% 16% 16% -- Average number used: 1.9 1.5 1.5 2.3 2.2 1.9 2.4 +0.5 n = 99-108 76-89 127-134 102 65-74 46-62 31-41 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 101-500 FTE, mobile (64%) and non-mobile ethnography (59%) plus in-store/shopping observations (46%) are perennially the top three most-used observational methods; use of non-mobile ethnography increased from 39% to 59%; automated measures/people meters, 10% to 30%; and mobile ethnography, 45% to 64%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Ethnography (NOT mobile) 11% 34% 19% 33% 3% Mobile ethnography 21% 38% 5% 25% 11% In-store/shopping observations 17% 22% 13% 43% 6% Passive metering 4% 12% 23% 43% 17% Automated measures/people meters 7% 5% 18% 57% 13% Wearables 6% 9% 14% 58% 14% n (range) = 45-61 Takeaway: Among service-led suppliers with 21-100 FTE, the observational methods with the most potential are automated measures/people meters (only 40% who will probably use it currently do) and passive metering (42%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Mobile ethnography 49% 48% 43% 49% 51% 42% 59% +17% Ethnography (NOT mobile) -- -- -- 50% 49% 37% 44% +7% In-store/shopping observations 71% 54% 50% 57% 50% 37% 39% +2% Passive metering 22% 21% 18% 28% 45% -- 16% -- Internet of Things (IoT) -- -- -- 20% 23% 11% -- -- Sensor/usage/telemetry -- -- -- 13% 21% 10% -- -- Wearables -- -- -- 17% 19% 14% 15% +1% Automated measures/people meters 21% 29% 26% 24% 17% 10% 12% +2% Average number used: 1.6 1.5 1.4 2.3 2.3 1.6 1.9 +0.3 n = 150-169 112-130 142-145 184 88-109 78-91 45-61 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 21-100 FTE, mobile (59%) and non-mobile ethnography (44%) plus in-store/shopping observations (39%) are perennial top three most-used observational methods; use of mobile ethnography increased from 42% to 59%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Ethnography (NOT mobile) 12% 32% 17% 36% 2% In-store/shopping observations 13% 26% 17% 40% 3% Mobile ethnography 10% 21% 21% 40% 7% Automated measures/people meters 2% 9% 16% 58% 16% Passive metering 2% 9% 13% 65% 10% Wearables 2% 5% 16% 61% 16% n (range) = 91-108 Takeaway: Among service-led suppliers with ≤20 FTE, the observational methods with the most potential are wearables (only 28% who will probably use it currently do), automated measures/people meters (40%), and passive metering (46%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Ethnography (NOT mobile) -- -- -- 51% 40% 45% 44% -1% In-store/shopping observations 62% 58% 45% 52% 38% 48% 39% -9% Mobile ethnography 35% 36% 39% 45% 34% 35% 31% -4% Automated measures/people meters 13% 15% 16% 9% 10% 11% 11% -- Passive metering 9% 13% 12% 17% 21% -- 11% -- Internet of Things (IoT) -- -- -- 11% 14% 14% -- -- Sensor/usage/telemetry -- -- -- 6% 10% 11% -- -- Wearables -- -- -- 9% 5% 8% 6% -2% Average number used: 1.2 1.2 1.1 1.8 1.5 1.7 1.4 -0.3 n = 54-97 185-221 234-239 271 116-130 133-150 91-108 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with ≤20 FTE, mobile (31%) and non-mobile ethnography (44%) plus in-store/shopping observations (39%) are perennial top three most-used observational methods. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC INTERPRETATION] Unlike survey, qual, and sample, observational research has no mainstream workhorse anchor; its methods are inherently occasional-use, deployed for specific purposes rather than embedded in routine practice — a structural feature of the category, not a sign of decline. What looks like decline is mostly a redistribution of users: brand-side researchers and tech-led suppliers are pulling back, while the segments with the greatest functional need — brand-side analytics and mid-to-large service-led suppliers serving CX, UX, and shopper work — are expanding. The brand-side split is stark: analytics professionals increased use of essentially every observational method this year (mobile ethnography +19%, in-store +17%), while researchers mostly declined, leaving analytics using roughly twice as many observational methods. GRIT hypothesizes, but cannot prove, that some researchers are migrating into the analytics segment as CX/UX work grows. On the supplier side, the clearest trend is ethnography expanding among mid-size and large service-led suppliers. Passive metering and automated measurement show a pronounced scale pattern, concentrated among the largest suppliers and brand analytics, where the necessary infrastructure or data already exists. Wearables appear in every segment but never break through, and in-store observation has been in gradual multi-year decline. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Biometrics & Neuroscience In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across six biometrics and neuroscience methods. IS NOW THE TIME FOR BIOMETRICS AND NEUROSCIENCE? [ORIENTATION] THREE MOST-USED BIOMETRIC & NEUROSCIENCE METHODS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Eye tracking 29% 27% 13% 10% 35% 43% 47% Emotion & affect analytics 25% 39% 32% 20% 38% 50% 45% Facial coding/facial expression analysis 19% 25% 13% 9% 26% 33% 39% Sensory research or testing 19% 37% 11% 23% 37% 33% 29% Biometric measures 14% 39% 5% 6% 13% 19% 27% Neuroscience 11% 28% 14% 7% 19% 23% 41% n (range) = 108-120 89-103 25-26 101-106 44-53 33-38 33-46 Green shading indicates top three most-used methodologies. Takeaway: Emotion and affect analytics is a top three most-used method in each segment; eye tracking is in the top three in each segment except for brand-side analytics (27%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Facial coding/facial expression analysis +4% +5% -3% 0% +6% +4% -6% Eye tracking +2% -5% -12% -2% +9% +4% +2% Sensory research or testing +1% -1% -1% -5% +4% +5% -12% Neuroscience 0% +8% +5% 1% +5% +10% +17% n (range) = 108-120 89-103 25-26 101-106 44-53 33-38 33-46 Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: Neuroscience increased by at least +5% in five segments. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 BIO & NEURO SCIENCE METHODS 2026 Method 2025 Precedent 2025 Family Biometric measures (e.g., GSR, HRV) Galvanic skin response (GSR) + Heart rate variability (HRV) (merged) Bio & Neuro Sciences Emotion & affect analytics (e.g., across video, audio, text, biometrics) NEW 2026 N/A Eye tracking Eye tracking Bio & Neuro Sciences Facial coding/facial expression analysis Facial coding and analysis Bio & Neuro Sciences Neuroscience (measures of neural activity) Neuroscience (measures of neural activity) Bio & Neuro Sciences Sensory research or testing Sensory research or testing Other Methods Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT Research Analytics Research - analytics Eye tracking 29% 27% +2% Emotion & affect analytics 25% 39% -14% Facial coding/facial expression analysis 19% 25% -6% Sensory research or testing 19% 37% -18% Biometric measures 14% 39% -25% Neuroscience 11% 28% -17% Average number used: 1.2 1.9 -0.7 n (range) = 108-120 89-103 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more biometric and neuroscience methods than researchers on average (1.9 vs. 1.2), with the largest gaps in biometric measures (39% vs. 14%), sensory research or testing (37% vs. 19%), and neuroscience (28% vs. 11%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Emotion & affect analytics 11% 14% 33% 35% 7% Eye tracking 7% 22% 12% 56% 3% Sensory research or testing 11% 8% 18% 56% 7% Facial coding/facial expression analysis 5% 14% 14% 65% 2% Neuroscience 2% 9% 17% 62% 9% Biometric measures 4% 10% 14% 66% 7% n (range) = 108-120 Takeaway: Among brand-side researchers, the biometric or neuroscience methods with the most potential are neuroscience (only 40% of probable users currently do) and emotion & affect analytics (43%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Eye tracking 36% 33% 35% 30% 27% 28% 29% +1% Emotion & affect analytics -- -- -- -- -- -- 25% -- Sensory research or testing -- -- -- 27% 28% 18% 19% +1% Facial coding/facial expression analysis 23% 19% 23% 26% 22% 15% 19% +4% Biometric measures 14% 27% 19% 10% -- -- 14% -- Galvanic skin response (GSR) -- -- -- 7% 3% 2% -- -- Heart rate variability (HRV) -- -- -- 7% 9% 1% -- -- Neuroscience 31% 32% 28% 20% 15% 13% 11% -2% Average number used: 1.0 1.1 1.0 1.2 1.0 0.8 1.2 +0.4 n (range) = 298 207 182-188 214 114-130 123-132 108-120 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among brand-side researchers, eye tracking (29%) and sensory research or testing (19%) have been top three most-used methods each year, and facial coding/facial expression analysis (19%) has been top-three for five of six years. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Emotion & affect analytics 14% 26% 37% 23% 1% Sensory research or testing 7% 30% 23% 32% 8% Biometric measures 13% 26% 21% 36% 4% Facial coding/facial expression analysis 8% 17% 31% 36% 8% Neuroscience 9% 19% 26% 38% 8% Eye tracking 7% 20% 19% 49% 6% n (range) = 89-103 Takeaway: Among brand-side analytics professionals, the biometric or neuroscience method with the most near-term potential is facial coding/facial expression analysis (only 44% of probable users currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Emotion & affect analytics -- -- -- 39% -- Biometric measures 13% -- -- 39% -- Heart rate variability (HRV) 12% 10% 12% -- -- Galvanic skin response (GSR) 7% 10% 8% -- -- Sensory research or testing 28% 44% 37% 37% -- Neuroscience 18% 20% 20% 28% +8% Eye tracking 27% 30% 32% 27% -5% Facial coding/facial expression analysis 20% 23% 20% 25% +5% Average number used: 1.1 1.4 1.3 1.9 +0.6 n (range) = 182 122-132 106-114 89-103 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among brand-side analytics professionals, sensory research or testing (37%) is a perennial top three most-used method; biometric measures (39%) and emotion and affect analytics (39%) are also in the top three. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics Sensory research or testing 56% 19% Emotion & affect analytics 42% 35% Biometric measures 28% 33% Facial coding/facial expression analysis 27% 30% Eye tracking 25% 25% Neuroscience 21% 32% n (range) = 108-120 89-103 Intensity = regular use/total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side researchers who use sensory research or testing use it regularly (56%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES; SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Eye tracking 13% 10% 35% 43% 47% Emotion & affect analytics 32% 20% 38% 50% 45% Neuroscience 14% 7% 19% 23% 41% Facial coding/facial expression analysis 13% 9% 26% 33% 39% Sensory research or testing 11% 23% 37% 33% 29% Biometric measures 5% 6% 13% 19% 27% Average number used: 0.9 0.8 1.7 2.0 2.3 n = (range) 25-26 101-106 44-53 33-38 33-46 Green shading indicates top three most-used methodologies. Takeaway: In each supplier segment, eye tracking and emotion and affect analytics are among the top three most-used biometrics or neuroscience methods. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Facial coding/facial expression analysis 22% 19% 44% 50% 42% Neuroscience 19% 0% 51% 22% 37% Emotion & affect analytics 16% 19% 39% 33% 33% Sensory research or testing 26% 36% 56% 26% 32% Biometric measures 0% 30% 65% 10% 31% Eye tracking 0% 25% 33% 48% 30% n = (range) 25-26 101-106 44-53 33-38 33-46 Intensity = regular use/total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Among service-led suppliers with 21-100 FTE, most users of biometric measures (65%), sensory research or testing (56%), and neuroscience (51%) use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Emotion & affect analytics 5% 27% 18% 50% 0% Facial coding/facial expression analysis 3% 10% 25% 58% 4% Eye tracking 0% 13% 20% 64% 3% Neuroscience 3% 11% 9% 74% 3% Sensory research or testing 3% 9% 12% 74% 3% Biometric measures 0% 5% 5% 79% 11% n (range) = 25-26 Takeaway: Among tech-led suppliers, the biometrics or neuroscience methods with the most potential are facial coding/facial expression analysis (only 34% who will probably use it currently do), eye tracking (40%), and biometric measures (48%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Emotion & affect analytics -- -- -- -- -- -- 32% -- Neuroscience 24% 20% 19% 9% 24% 9% 14% +5% Eye tracking 15% 20% 22% 31% 38% 25% 13% -12% Facial coding/facial expression analysis 12% 24% 21% 22% 26% 16% 13% -3% Sensory research or testing -- -- -- 14% 25% 13% 11% -2% Biometric measures 5% 11% 13% 13% -- -- 5% -- Heart rate variability (HRV) -- -- -- 10% 19% 16% -- -- Galvanic skin response (GSR) -- -- -- 10% 9% 8% -- -- Average number used: 0.6 0.7 0.8 1.0 1.4 0.9 0.9 -- n (range) = 97 46-50 122-125 70 32-47 27-37 25-26 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among tech-led suppliers, eye tracking (13%) and facial coding/facial expression analysis (13%) are perennially among the three most-used methods; use of eye tracking fell from 25% to 13%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Emotion & affect analytics 15% 30% 33% 22% 0% Eye tracking 14% 33% 18% 31% 4% Facial coding/facial expression analysis 17% 23% 25% 34% 2% Neuroscience 15% 26% 13% 42% 4% Sensory research or testing 9% 20% 19% 47% 4% Biometric measures 8% 19% 13% 53% 7% n (range) = 33-46 Takeaway: Among service-led suppliers with 500+ FTE, the biometric or neuroscience method with the most potential is emotion and affect analytics (only 58% who will probably use it currently do); each other method is at least 61% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Eye tracking 56% 36% 54% 48% 52% 44% 47% +3% Emotion & affect analytics -- -- -- -- -- -- 45% -- Neuroscience 50% 36% 49% 39% 30% 24% 41% +17% Facial coding/facial expression analysis 44% 31% 41% 46% 43% 45% 39% -6% Sensory research or testing -- -- -- 32% 35% 42% 29% -13% Biometric measures 24% 32% 40% 19% -- -- 27% -- Heart rate variability (HRV) -- -- -- 15% 18% 14% -- -- Galvanic skin response (GSR) -- -- -- 13% 15% 9% -- -- Average number used: 1.2 1.0 1.3 1.9 1.4 1.3 1.8 +0.5 n (range) = 106 85-88 117-129 97 60-73 59-67 33-46 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 500+ FTE, eye tracking (47%) is perennially the most-used method, and neuroscience (41%) has been among the top three in four of six years; use of neuroscience increased from 24% to 41% and use of sensory research or testing fell from 42% to 29%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Emotion & affect analytics 17% 33% 30% 13% 7% Eye tracking 21% 22% 22% 35% 0% Facial coding/facial expression analysis 16% 16% 25% 42% 0% Neuroscience 5% 18% 22% 44% 11% Sensory research or testing 9% 24% 11% 51% 5% Biometric measures 2% 17% 17% 55% 9% n (range) = 33-38 Takeaway: Among service-led suppliers with 101-500 FTE, the biometrics or neuroscience method with the most potential is neuroscience (only 51% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Emotion & affect analytics -- -- -- -- -- -- 50% -- Eye tracking 57% 49% 46% 48% 31% 39% 43% +4% Neuroscience 45% 35% 30% 14% 20% 13% 23% +10% Facial coding/facial expression analysis 35% 20% 33% 30% 32% 29% 33% +4% Sensory research or testing -- -- -- 33% 29% 27% 33% +6% Biometric measures 20% 25% 27% 7% -- -- 19% -- Heart rate variability (HRV) -- -- -- 5% 9% 8% -- -- Galvanic skin response (GSR) -- -- -- 4% 9% 3% -- -- Average number used: 1.6 1.3 1.4 1.3 1.3 1.2 2.0 +0.8 n (range) = 108 81-89 127-134 102 93-104 48-62 33-38 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 101-500 FTE, eye tracking (43%) is perennially among the top three most-used biometrics or neuroscience methods; use of neuroscience increased from 13% to 23%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Eye tracking 12% 24% 21% 37% 6% Facial coding/facial expression analysis 11% 14% 28% 41% 5% Emotion & affect analytics 15% 23% 16% 37% 9% Sensory research or testing 20% 16% 17% 42% 5% Neuroscience 10% 9% 12% 60% 9% Biometric measures (e.g., GSR, HRV) 9% 5% 13% 62% 11% n (range) = 44-53 Takeaway: Among service-led suppliers with 21-100 FTE, the biometrics or neuroscience method with the most potential is facial coding/facial expression analysis (only 48% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Emotion & affect analytics -- -- -- -- -- -- 38% -- Sensory research or testing -- -- -- 25% 23% 33% 37% +4% Eye tracking 36% 32% 36% 37% 34% 26% 35% +9% Facial coding/facial expression analysis 20% 24% 20% 27% 29% 20% 26% +6% Neuroscience 29% 27% 26% 17% 13% 14% 19% +5% Biometric measures 14% 25% 19% 11% -- -- 13% -- Heart rate variability (HRV) -- -- -- 8% 11% 5% -- -- Galvanic skin response (GSR) -- -- -- 8% 10% 6% -- -- Average number used: 1.0 1.1 1.0 1.2 1.2 1.0 1.7 +0.7 n (range) = 169 122-130 142-145 184 86-104 81-95 44-53 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with 21-100 FTE, eye tracking (35%) is perennially among the top three most-used biometrics or neuroscience methods. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Emotion & affect analytics 4% 17% 17% 53% 9% Sensory research or testing 8% 15% 11% 60% 6% Eye tracking 3% 8% 15% 73% 2% Facial coding/facial expression analysis 2% 7% 15% 66% 10% Neuroscience 0% 7% 13% 68% 12% Biometric measures 2% 4% 10% 73% 11% n (range) = 101-106 Takeaway: Among service-led suppliers with ≤20 FTE, the biometrics or neuroscience methods with the most potential are neuroscience (34% saturated), biometric measures (36%), facial coding/facial expression analysis (38%), and eye tracking (41%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Sensory research or testing -- -- -- 26% 21% 28% 23% -5% Emotion & affect analytics -- -- -- -- -- -- 20% -- Eye tracking 24% 29% 25% 29% 21% 12% 10% -2% Facial coding/facial expression analysis 6% 17% 15% 14% 12% 9% 9% -- Neuroscience 16% 24% 22% 16% 12% 6% 7% +1% Biometric measures 5% 16% 14% 7% -- -- 6% -- Heart rate variability (HRV) -- -- -- 5% 1% 1% -- -- Galvanic skin response (GSR) -- -- -- 7% 4% 1% -- -- Average number used: 0.5 0.9 0.8 1.0 0.5 0.3 0.5 +0.2 n (range) = 310 194-221 234-239 271 118-133 134-160 101-106 Green shading indicates top three methodologies for that GRIT wave. Net percentages cannot be calculated since 24A due to randomization of questions. Takeaway: Among service-led suppliers with ≤20 FTE, Sensory research or testing (23%) has been among the top three most-used biometrics or neuroscience methods each year. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC INTERPRETATION] Biometrics and neuroscience are undergoing structural consolidation — neither a decline nor a mainstream breakthrough, but a sorting into the hands of organizations that can deploy these methods at scale. The segments expanding use are precisely those with the necessary infrastructure: service-led suppliers with 101–500 and 500+ FTE are growing across nearly every method, and neuroscience is recovering in those segments even as it erodes among smaller and tech-led suppliers. This pattern suggests the constraint on adoption is not awareness or interest but the operational and cost requirements of running these methods reliably. Whether larger suppliers scaling them will eventually widen access or keep them as differentiated offerings is an open question; that smaller suppliers are exiting while larger ones invest suggests the gap may widen before it narrows, if it narrows at all. The debut of emotion and affect analytics may be the first method in this family to begin crossing the accessibility threshold, since AI-mediated analysis of video, audio, and text requires far less specialized hardware than EEG or eye-tracking. Sensory research is distinct, indexing toward mid-size suppliers rather than the largest (it fell −13% to 29% among 500+ FTE), and is used intensely by the relatively few brand-side researchers — 56% regular users — whose categories, such as CPG, food, and beverage, depend on it. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Data & Analytics In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across nine methods related to data and analytics. HOW ARE DATA AND ANALYTICS GROWING ACROSS INSIGHTS? [ORIENTATION] THREE MOST-USED DATA & ANALYTICS METHODS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Text analytics 68% 77% 82% 61% 76% 70% 91% Social media and online content research 63% 86% 69% 29% 55% 55% 80% Data integration 59% 88% 54% 44% 52% 80% 72% Big Data analytics 46% 86% 48% 31% 39% 63% 70% Attribution analytics/single source data 35% 87% 43% 21% 29% 52% 53% Causal analysis 34% 74% 56% 35% 44% 63% 64% n (range) = 93-117 82-109 16-27 87-103 41-53 27-40 27-38 Green shading indicates top three most-used methodologies. Takeaway: Text analytics is a top three most-used data and analytics method in each segment except brand-side analytics (77%), and data integration is top-three in all but tech-led suppliers (54%); social media and online content research is top-three in all except service-led suppliers with ≤20 FTE (29%) and with 101-500 FTE (55%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Synthetic data +18% +13% +1% +14% +7% +18% +1% Text analytics +8% -3% -1% -2% +4% -2% -1% Data integration +6% -5% -7% -5% -9% +15% -7% Social media and online content research +4% +5% +36% -1% +5% +8% +36% Meta-analysis -4% -5% +13% +2% +1% +23% +13% Causal analysis -5% -7% +20% -7% -10% +26% +20% Big Data analytics -7% -3% -8% -3% -1% +29% -8% Attribution analytics/single source data -9% +9% +8% -16% -13% +6% +8% n (range) = 93-117 82-109 16-27 87-103 41-53 27-40 27-38 Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: Synthetic data increased by at least +10% in four segments. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 DATA & ANALYTICS METHODS 2026 Method 2025 Precedent 2025 Family Attribution analytics/single source data Attribution analytics/single source data Data & Analytics Big Data analytics Big Data analytics Data & Analytics Causal analysis Causal analysis Data & Analytics Data integration Data integration Data & Analytics Meta-analysis Meta-analysis Data & Analytics Social media and online content research Social media analytics + Monitoring blogs (merged) Data & Analytics, Observational Synthetic data (e.g., synthetic sample, AI personas/digital twins) Synthetic sample Data & Analytics Text analytics Text analytics Data & Analytics Video analytics/computer vision for research NEW 2026 N/A Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT Research Analytics Research - analytics Text analytics 68% 77% -9% Social media and online content research 63% 86% -23% Data integration 59% 88% -29% Big Data analytics 46% 86% -40% Meta-analysis 38% 63% -25% Attribution analytics/single source data 35% 87% -52% Causal analysis 34% 74% -40% Synthetic data 26% 57% -31% Video analytics/computer vision for research 15% 56% -41% Average number used: 3.8 6.7 -2.9 n (range) = 93-117 82-109 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more data and analytics methods than researchers on average (6.7 vs. 3.8), with the largest gaps in attribution analytics/single source data (87% vs. 35%), Big Data analytics (86% vs. 46%), video analytics/computer vision for research (56% vs. 15%), and causal analysis (74% to 34%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Text analytics 38% 30% 25% 6% 1% Social media and online content research 28% 35% 25% 10% 2% Data integration 27% 32% 26% 7% 8% Big Data analytics 27% 19% 30% 17% 7% Synthetic data 8% 17% 40% 33% 1% Attribution analytics/single source data 14% 21% 28% 18% 18% Causal analysis 12% 22% 28% 20% 18% Meta-analysis 12% 26% 17% 26% 20% Video analytics/computer vision for research 4% 11% 30% 37% 19% n (range) = 93-117 Takeaway: Among brand-side researchers, the data and analytics methods with the most potential are video analytics/computer vision for research (only 33% of probable users currently do) and synthetic data (39%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Text analytics 53% 47% 49% 63% 60% 60% 68% +8% Social media and online content research 68% 58% 53% 66% 57% 59% 63% +4% Data integration -- 38% 47% 65% 63% 53% 59% +6% Big Data analytics 58% 43% 36% 46% 49% 53% 46% -7% Meta-analysis -- -- -- 31% 40% 42% 38% -4% Attribution analytics/single source data 23% 23% 20% 39% 58% 44% 35% -9% Causal analysis 33% 37% 30% 53% 44% 38% 34% -4% Synthetic data -- -- -- -- 8% 8% 26% +18% Video analytics/computer vision for research -- -- -- -- -- -- 15% -- Average number used: 2.3 2.5 2.4 3.6 3.8 3.6 3.8 +0.2 n (range) = 298 207 182 214 190 107-137 93-117 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side researchers, text analytics (68%) is a perennial top three most-used data and analytics method, and social media and online content research (63%) and data integration (59%) have been in each year but one; use of synthetic data has increased from 8% to 26%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Social media and online content research 54% 33% 13% 1% 0% Data integration 60% 28% 9% 2% 0% Big Data analytics 61% 25% 11% 2% 1% Causal analysis 42% 32% 20% 2% 4% Text analytics 39% 38% 17% 5% 1% Attribution analytics/single source data 45% 42% 7% 4% 3% Meta-analysis 23% 41% 27% 6% 4% Synthetic data 29% 28% 31% 7% 5% Video analytics/computer vision for research 26% 30% 23% 22% 0% n (range) = 82-109 Takeaway: Among brand-side analytics professionals, the data and analytics method with the most potential is synthetic data (only 64% of probable users currently do); each other method is at least 70% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Data integration 88% 87% 94% 88% -6% Attribution analytics/single source data 71% 68% 78% 87% +9% Social media and online content research 66% 67% 82% 86% +4% Big Data analytics 75% 80% 89% 86% -3% Text analytics 68% 74% 80% 77% -3% Causal analysis 68% 58% 81% 74% -7% Meta-analysis 61% 63% 68% 63% -5% Synthetic data -- 35% 43% 57% +14% Video analytics/computer vision for research -- -- -- 56% -- Average number used: 5.0 5.3 6.1 6.7 +0.6 n (range) = 182 194 103-130 82-109 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side analytics professionals, data integration (88%) and Big Data analytics (86%) are perennial top three most-used methods; use of synthetic data increased from 43% to 57%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics Big Data analytics 58% 71% Text analytics 55% 51% Data integration 45% 68% Social media and online content research 44% 62% Attribution analytics/single source data 40% 52% Causal analysis 34% 57% Synthetic data 32% 50% Meta-analysis 32% 36% Video analytics/computer vision for research 24% 46% n (range) = 93-117 82-109 Intensity = regular use/total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side insights professionals who use Big Data analytics use it regularly (58% of researchers and 71% of analytics), and the same is true for text analytics (55% and 51%, respectively); for analytics professionals, at least half of their use of five other methods is regular use. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Text analytics 82% 61% 76% 70% 91% Social media and online content research 69% 29% 55% 55% 80% Data integration 54% 44% 52% 80% 72% Big Data analytics 48% 31% 39% 63% 70% Causal analysis 56% 35% 44% 63% 64% Meta-analysis 49% 32% 34% 62% 54% Attribution analytics/single source data 43% 21% 29% 52% 53% Synthetic data 22% 16% 16% 34% 44% Video analytics/computer vision for research 24% 12% 28% 28% 42% Average number used: 4.5 2.8 3.7 5.1 5.7 n (range) = 16-27 87-103 41-53 27-40 27-38 Green shading indicates top three most-used methodologies. Takeaway: In each supplier segment, text analytics is the most-used data and analytics method; Data integration is in the top three in each segment except tech-led suppliers. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Text analytics 62% 50% 59% 68% 67% Big Data analytics 50% 29% 50% 28% 63% Data integration 42% 42% 48% 37% 56% Causal analysis 73% 40% 38% 47% 53% Meta-analysis 67% 35% 47% 56% 53% Synthetic data 44% 18% 30% 14% 49% Social media and online content research 27% 25% 30% 54% 46% Video analytics/computer vision for research 62% 47% 42% 54% 42% Attribution analytics/single source data 67% 23% 50% 43% 33% n (range) = 16-27 87-103 41-53 27-40 27-38 Intensity = regular use/total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: At least half of the users of text analytics in each segment use it regularly. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Text analytics 51% 31% 13% 5% 0% Social media and online content research 19% 50% 18% 13% 0% Meta-analysis 33% 16% 26% 24% 0% Attribution analytics/single source data 29% 14% 29% 24% 4% Causal analysis 41% 15% 15% 29% 0% Big Data analytics 24% 24% 17% 26% 9% Synthetic data 10% 13% 19% 50% 9% Video analytics/computer vision for research 15% 9% 12% 48% 16% Data integration 23% 31% 41% 5% 0% n (range) = 16-27 Takeaway: Among tech-led suppliers, the data and analytics methods with the most potential are synthetic data (only 54% who will probably use it currently do), and data integration (57%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Text analytics 53% 76% 62% 78% 68% 83% 82% -1% Social media and online content research 68% 40% 39% 46% 41% 33% 69% +36% Causal analysis 23% 26% 32% 41% 33% 36% 56% +20% Data integration -- 60% 59% 80% 72% 61% 54% -7% Meta-analysis -- -- -- 35% 46% 37% 49% +12% Big Data analytics 39% 48% 43% 40% 66% 56% 48% -8% Attribution analytics/single source data 23% 34% 30% 46% 44% 35% 43% +8% Video analytics/computer vision for research -- -- -- -- -- -- 24% -- Synthetic data -- -- -- -- 16% 22% 22% -- Average number used: 2.1 2.8 2.6 3.7 3.9 3.6 4.5 +0.9 n (range) = 97 50 122-125 70 35-40 30-37 16-27 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among tech-led suppliers, text analytics (82%) is perennially among the most-used methods; use of social media and online content research rose from 33% to 69%; causal analysis, 36% to 56%; and meta-analysis, 37% to 49%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Text analytics 61% 30% 7% 2% 0% Data integration 40% 32% 20% 0% 8% Social media and online content research 37% 43% 7% 10% 3% Big Data analytics 44% 26% 15% 8% 7% Meta-analysis 28% 26% 28% 3% 15% Synthetic data 22% 22% 36% 13% 7% Causal analysis 23% 41% 11% 10% 14% Video analytics/computer vision for research 18% 24% 20% 21% 17% Attribution analytics/single source data 17% 36% 3% 12% 32% n (range) = 27-38 Takeaway: Among service-led suppliers with 500+ FTE, the data and analytics method with the most potential is synthetic data (only 55% who will probably use it currently do); each other method is at least 66% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Text analytics 75% 66% 62% 77% 71% 91% 91% -- Social media and online content research 72% 53% 56% 68% 71% 70% 80% +10% Data integration -- 62% 69% 71% 76% 77% 72% -5% Big Data analytics 68% 55% 54% 64% 72% 60% 70% +10% Causal analysis 45% 41% 45% 57% 45% 53% 64% +11% Meta-analysis -- -- -- 56% 49% 56% 54% -2% Attribution analytics/single source data 32% 49% 45% 58% 47% 65% 53% -12% Synthetic data -- -- -- -- 21% 26% 44% +18% Video analytics/computer vision for research -- -- -- -- -- -- 42% -- Average number used: 2.9 3.3 3.3 4.5 4.5 5.0 5.7 +0.7 n (range) = 106 85 117-129 97 63-79 58-69 27-38 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 500+ FTE, data integration (72%) is perennially among the three most-used methods, text analytics (91%) and social media and online content research (80%) have been in all but one year; use of synthetic data increased from 26% to 44%; causal analysis, 53% to 64%; Big Data analytics, 60% to 70%; and social media and online content, 70% to 80%. Attribution analytics/single source data use fell from 65% to 53%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Text analytics 48% 22% 21% 7% 2% Data integration 30% 51% 8% 2% 10% Social media and online content research 30% 25% 27% 17% 0% Causal analysis 30% 33% 14% 2% 21% Big Data analytics 18% 45% 13% 10% 14% Meta-analysis 35% 27% 13% 9% 15% Synthetic data 5% 29% 36% 23% 7% Video analytics/computer vision for research 15% 13% 32% 18% 22% Attribution analytics/single source data 22% 29% 6% 6% 36% n (range) = 27-40 Takeaway: Among service-led suppliers with 101-500 FTE, the data and analytics methods with the most potential are video analytics/computer vision for research (only 46% who will probably use it currently do) and synthetic data (48%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Data integration -- 66% 62% 79% 83% 65% 80% +15% Text analytics 59% 58% 64% 73% 70% 73% 70% -3% Big Data analytics 62% 43% 41% 47% 59% 35% 63% +28% Causal analysis 36% 39% 29% 55% 55% 37% 63% +26% Meta-analysis -- -- -- 47% 45% 39% 62% +23% Social media and online content research 57% 60% 49% 54% 53% 48% 55% +7% Attribution analytics/single source data 32% 34% 34% 50% 69% 46% 52% +6% Synthetic data -- -- -- -- 19% 16% 34% +18% Video analytics/computer vision for research -- -- -- -- -- -- 28% -- Average number used: 2.5 3.0 2.8 4.1 4.5 3.6 5.1 +1.5 n (range) = 108 89 127-134 102 69-74 46-61 27-40 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 101-500 FTE, data integration (80%) and text analytics (70%) are perennially among the top three most-used data and analytics methods; use of Big Data analytics increased from 35% to 63%; causal analysis, 37% to 63%; meta-analysis, 39% to 62%; synthetic data, 16% to 34%; and data integration, 65% to 80%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Text analytics 45% 31% 13% 7% 3% Data integration 25% 27% 22% 18% 9% Social media and online content research 16% 38% 10% 33% 3% Causal analysis 17% 27% 20% 20% 16% Synthetic data 5% 11% 46% 29% 9% Big Data analytics 20% 20% 21% 28% 12% Video analytics/computer vision for research 12% 16% 29% 32% 11% Meta-analysis 16% 18% 23% 25% 19% Attribution analytics/single source data 14% 15% 23% 22% 26% n (range) = 41-53 Takeaway: Among service-led suppliers with 21-100 FTE, the data and analytics methods with the most potential is synthetic data (only 26% who will probably use it currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Text analytics 52% 48% 52% 67% 70% 73% 76% +3% Social media and online content research 46% 35% 39% 50% 39% 50% 55% +5% Data integration -- 48% 56% 71% 63% 60% 52% -8% Causal analysis 26% 30% 31% 55% 42% 54% 44% -10% Big Data analytics 35% 34% 37% 38% 42% 40% 39% -1% Meta-analysis -- -- -- 40% 42% 33% 34% +1% Attribution analytics/single source data 18% 25% 27% 49% 44% 42% 29% -13% Video analytics/computer vision for research -- -- -- -- -- -- 28% -- Synthetic data -- -- -- -- 14% 9% 16% +7% Average number used: 1.8 2.2 2.4 3.7 3.6 3.6 3.7 +0.1 n (range) = 169 130 142-145 184 98-118 74-93 41-53 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 21-100 FTE, text analytics (76%) and data integration (52%) are perennial top three most-used data and analytics methods; use of attribution analytics/single source data fell from 42% to 29% and causal analysis fell from 54% to 44%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Text analytics 31% 31% 24% 13% 1% Data integration 18% 25% 32% 16% 8% Social media and online content research 7% 22% 32% 33% 6% Meta-analysis 11% 21% 26% 30% 12% Big Data analytics 9% 22% 20% 39% 9% Causal analysis 14% 21% 17% 30% 18% Attribution analytics/single source data 5% 17% 22% 38% 19% Synthetic data 3% 13% 26% 53% 5% Video analytics/computer vision for research 5% 6% 21% 56% 12% n (range) = 87-103 Takeaway: Among service-led suppliers with ≤20 FTE, the data and analytics methods with the most potential are video analytics/computer vision for research (only 36% who will probably use it currently do) and synthetic data (38%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Text analytics 37% 38% 43% 56% 56% 63% 61% -2% Data integration -- 32% 35% 56% 42% 49% 44% -5% Causal analysis 26% 31% 30% 49% 38% 41% 35% -6% Meta-analysis -- -- -- 36% 28% 30% 32% +2% Big Data analytics 24% 27% 26% 37% 37% 34% 31% -3% Social media and online content research 34% 31% 32% 45% 32% 30% 29% -1% Attribution analytics/single source data 13% 16% 18% 38% 28% 38% 21% -17% Synthetic data -- -- -- -- 5% 3% 16% +13% Video analytics/computer vision for research -- -- -- -- -- -- 12% -- Average number used: 1.3 1.7 1.8 3.2 2.7 2.9 2.8 -0.1 n (range) = 97 221 234-239 271 108-140 140-156 87-103 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with ≤20 FTE, text analytics (61%) and data integration (44%) are perennial top three most-used data and analytics methods, and causal analysis (35%) has been every year but one; use of synthetic data increased from 3% to 16% while attribution analytics/single source data fell from 38% to 21%. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC INTERPRETATION] Data and analytics methods are transitioning from specialties to an infrastructure layer, but unevenly: the industry is stratifying, with the most analytically capable segments pulling further ahead while the gap to smaller and less specialized segments widens on the more demanding methods. Text analytics and data integration have already completed the transition — embedded everywhere at high intensity, they form the baseline. A layer up, causal analysis, Big Data analytics, and meta-analysis are intermediate: well-established in larger, more sophisticated segments and still gaining elsewhere. Synthetic data and video analytics occupy the frontier. Synthetic data rose by double digits in four segments and has grown consistently; an expanded label (AI personas, digital twins) contributed, but the trajectory is meaningful and low saturation leaves runway. Not every method diffuses — attribution analytics appears to consolidate instead, thriving where data infrastructure is rich and losing relevance where it isn’t. Brand-side analytics functions as a leading indicator, averaging 6.7 methods at near-universal adoption and high intensity — a picture of where the rest of the industry may be heading. The most active movers are service-led suppliers with 101–500 FTE, where five methods rose by double digits, including analytically demanding ones such as causal analysis and meta-analysis, suggesting a deliberate move up the analytical value chain rather than a response to client demand alone. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Other Methodologies In this section, we explore use, adoption momentum, intensity of use, and saturation of potential across nine methods or approaches related to insights that do not fit cleanly into survey, focus groups and IDI’s, sample, observational research, biometrics or neuroscience, or data and analytics. WHAT ELSE GROWS BEYOND THE CORE? [ORIENTATION] THREE MOST-USED “OTHER” METHODOLOGIES: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Software or tools marketplaces 50% 85% 54% 54% 54% 36% 54% Sample marketplaces 46% 69% 70% 59% 68% 62% 68% Prediction markets 30% 66% 21% 16% 21% 34% 43% Behavioral economics models 29% 66% 26% 30% 38% 44% 44% Talent marketplaces 27% 70% 46% 36% 32% 38% 45% Research gamification 18% 56% 44% 21% 35% 45% 48% n (range) = 105-176 82-152 26-39 96-158 44-79 33-56 32-55 Green shading indicates top three most-used methodologies. Takeaway: Sample marketplaces are a top three most-used “other” method in each segment, and software or tools marketplaces is among the top three in each supplier segment except service-led suppliers with 101-500 FTE (36%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGE IN USE OF METHODS/APPROACHES SINCE 25A: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Crowdsourcing +14% +9% +13% +12% +17% +12% +13% Research gamification +1% +6% +4% -6% 0% +9% -9% Sample marketplaces -1% +9% +1% +6% +2% -10% +7% Prediction markets -1% -3% -12% -5% -7% +3% +1% Software or tools marketplaces -3% +3% -1% +9% +6% -9% +8% Behavioral economics models -4% +5% +3% -8% -3% +2% -7% Talent marketplaces -6% -6% +10% +13% -5% +2% +6% n (range) = 105-176 82-152 26-39 96-158 44-79 33-56 32-55 Green indicates relatively larger increases; red indicates relatively larger decreases. Color scale applies across all segments. Takeaway: Crowdsourcing increased at least +5% in each segment, while each type of marketplace increased in three segments while declining in at least one. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CHANGES FROM 2025 GRIT SURVEY 2026 OTHER METHODS 2026 Method 2025 Precedent 2025 Family Behavioral economics models Behavioral economics models Other Methods Crowdsourcing (ideas/problem-solving) Crowdsourcing Other Methods Marketplaces for sample Marketplaces for sample Other Methods Marketplaces for software or tools Marketplaces for software or tools Other Methods Marketplaces for talent Marketplaces for talent Other Methods Prediction markets Prediction markets Other Methods Research gamification Research gamification Other Methods Semiotics/cultural decoding NEW 2026 N/A VR/AR/XR for research (e.g., concept, shopper, environment testing) VE/VR + AI or VR/AR/XR for CX/UX design (consolidated) Other Methods Green indicates method changed from 25A. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | BRAND POV [DATA] USE OF METHODS/APPROACHES: BRAND SEGMENT Research Analytics Research - analytics Software or tools marketplaces 50% 85% -35% Sample marketplaces 46% 69% -23% Prediction markets 30% 66% -36% Behavioral economics models 29% 66% -37% VR/AR/XR for research 27% 47% -20% Talent marketplaces 27% 70% -43% Crowdsourcing 23% 53% -30% Semiotics/cultural decoding 19% 28% -9% Research gamification 18% 56% -38% Average number used: 2.7 5.4 -2.7 n (range) = 105-176 82-152 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals use more “other” methods than researchers on average (5.4 vs. 2.7), with the largest gaps in talent marketplaces (70% vs. 27%), research gamification (56% vs. 18%), behavioral economics models (66% to 29%), prediction markets (66% vs. 30%), and software or tools marketplaces (85% vs. 50%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: RESEARCH) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Software or tools marketplaces 31% 19% 12% 17% 20% Sample marketplaces 21% 25% 17% 15% 22% Crowdsourcing 8% 15% 33% 43% 1% Prediction markets 6% 24% 20% 39% 11% Behavioral economics models 9% 20% 20% 38% 13% VR/AR/XR for research 11% 16% 20% 47% 6% Research gamification 5% 13% 29% 48% 5% Talent marketplaces 10% 17% 19% 30% 24% Semiotics/cultural decoding 5% 14% 20% 41% 21% n (range) = 105-176 Takeaway: Among brand-side researchers, the “other” methods with the most potential are research gamification (only 38% of probable users currently do) and crowdsourcing (41%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A - 25A Marketplaces 18% 19% 15% 33% 54% -- -- -- Software or tools marketplaces -- -- -- -- -- 54% 50% -4% Sample marketplaces -- -- -- -- -- 46% 46% -- Talent marketplaces -- -- -- -- -- 32% 27% -5% Prediction markets 22% 18% 19% 35% 31% 31% 30% -1% Behavioral economics models 26% 32% 27% 35% 40% 33% 29% -4% VR/AR/XR for research -- -- -- -- -- -- 27% -- AI or VR/AR/XR for CX/UX design 60% 29% 20% 29% 26% 19% -- -- VE/VR 12% 14% 13% 10% 11% 8% -- -- Crowdsourcing 18% 21% 17% 20% 22% 10% 23% +13% Semiotics/cultural decoding -- -- -- -- -- -- 19% -- Research gamification 21% 18% 15% 25% 20% 17% 18% +1% Average number used: 1.8 1.5 1.3 1.9 2.0 2.5 2.7 +0.2 n (range) = 298 207 182 214 110-137 116-202 105-176 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side researchers, software or tools marketplaces (50%), sample marketplaces (46%), and prediction markets are the top three “other” methods; use of crowdsourcing increased from 10% to 23%. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (BRAND: ANALYTICS) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Software or tools marketplaces 55% 30% 12% 3% 1% Behavioral economics models 23% 43% 26% 6% 3% Research gamification 20% 36% 34% 10% 0% Prediction markets 26% 39% 20% 11% 3% Talent marketplaces 34% 36% 14% 11% 4% Sample marketplaces 30% 39% 10% 12% 9% Crowdsourcing 17% 36% 26% 20% 2% VR/AR/XR for research 9% 38% 24% 24% 5% Semiotics/cultural decoding 10% 18% 38% 22% 12% n (range) = 82-152 Takeaway: Among brand-side analytics professionals, the “other” method with the most potential is semiotics/cultural decoding (only 43% of probable users currently do). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Marketplaces 60% 71% -- -- -- Software or tools marketplaces -- -- 82% 85% +3% Talent marketplaces -- -- 76% 70% -6% Sample marketplaces -- -- 60% 69% +9% Prediction markets 60% 67% 69% 66% -3% Behavioral economics models 58% 53% 61% 66% +5% VR/AR/XR for research -- -- -- 47% -- VE/VR 22% 40% 31% -- -- AI or VR/AR/XR for CX/UX design 52% 31% 55% -- -- Research gamification 39% 46% 49% 56% +7% Crowdsourcing 41% 43% 44% 53% +9% Semiotics/cultural decoding -- -- -- 28% -- Average number used: 3.3 3.5 5.3 5.4 +0.1 n (range) = 182 84-127 101-177 82-152 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among brand-side analytics professionals, marketplaces for software or tools (85%), talent (70%), and sample (69%) are the most-used “other” methods. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. INTENSITY OF USE: BRAND SEGMENT Research Analytics Software or tools marketplaces 62% 65% Sample marketplaces 46% 44% VR/AR/XR for research 41% 19% Talent marketplaces 37% 49% Crowdsourcing 36% 32% Behavioral economics models 30% 35% Research gamification 27% 35% Semiotics/cultural decoding 27% 35% Prediction markets 21% 40% n (range) = 105-176 82-152 Intensity = regular use/total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: Most brand-side insights professionals who use software or tools marketplaces (62% for researchers, 65% for analytics) use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES AND USAGE TRENDS | SUPPLIER POV [DATA] USE OF METHODS/APPROACHES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Sample marketplaces 70% 59% 68% 62% 68% Software or tools marketplaces 54% 54% 54% 36% 54% Research gamification 44% 21% 35% 45% 48% Talent marketplaces 46% 36% 32% 38% 45% Semiotics/cultural decoding 20% 25% 17% 42% 44% Behavioral economics models 26% 30% 38% 44% 44% Prediction markets 21% 16% 21% 34% 43% Crowdsourcing 36% 22% 29% 28% 41% VR/AR/XR for research 30% 14% 28% 21% 26% Average number used: 3.5 2.8 3.2 3.5 4.1 n (range) = 26-39 96-158 44-79 33-56 32-55 Green shading indicates top three most-used methodologies. Takeaway: In each supplier segment, sample marketplaces is the most-used “other” method, and software or tools marketplaces is among the top three in all but service-led suppliers with 101-500 FTE (36%). Source: GRIT 2026 Insights Practice Report, Greenbook. INTENSITY OF USE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Sample marketplaces 72% 66% 71% 70% 66% Software or tools marketplaces 59% 50% 49% 50% 61% VR/AR/XR for research 62% 38% 46% 0% 45% Research gamification 36% 33% 40% 32% 44% Crowdsourcing 0% 15% 45% 22% 41% Behavioral economics models 62% 41% 61% 44% 33% Talent marketplaces 49% 30% 64% 34% 31% Prediction markets 55% 16% 54% 33% 22% Semiotics/cultural decoding 11% 19% 73% 27% 14% n (range) = 26-39 96-158 44-79 33-56 32-55 Intensity = regular use/total use. Green indicates relatively higher intensity; red indicates relatively lower intensity. Color scale applies across both segments. Takeaway: In each supplier segment, two-thirds or more of users of sample marketplaces use them regularly. Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES AND USAGE TRENDS | TECH-LED POV [DATA] INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (TECH-LED) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Sample marketplaces 51% 19% 8% 22% 0% Research gamification 16% 28% 22% 31% 3% Talent marketplaces 23% 23% 17% 22% 15% Software or tools marketplaces 32% 22% 6% 26% 14% Crowdsourcing 0% 36% 14% 36% 13% VR/AR/XR for research 18% 11% 16% 54% 0% Behavioral economics models 16% 10% 15% 53% 6% Prediction markets 12% 10% 18% 54% 7% Semiotics/cultural decoding 2% 17% 8% 58% 15% n (range) = 26-39 Takeaway: Among tech-led suppliers, the “other” method with the most potential is prediction markets (only 55% who will probably use it currently do); each other method has a saturation of at least 63%. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Marketplaces 38% 48% 43% 59% 68% -- -- -- Sample marketplaces -- -- -- -- -- 69% 70% +1% Software or tools marketplaces -- -- -- -- -- 55% 54% -1% Talent marketplaces -- -- -- -- -- 35% 46% +11% Research gamification 31% 42% 30% 52% 28% 41% 44% +3% Crowdsourcing 13% 22% 9% 26% 29% 23% 36% +13% VR/AR/XR for research -- -- -- -- -- -- 30% -- AI or VR/AR/XR for CX/UX design 54% 54% 45% 42% 28% 50% -- -- VE/VR 4% 4% 6% 16% 10% 10% -- -- Behavioral economics models 14% 18% 24% 36% 22% 23% 26% +3% Prediction markets 15% 18% 13% 30% 36% 34% 21% -13% Semiotics/cultural decoding -- -- -- -- -- -- 20% -- Average number used: 1.7 2.1 1.7 2.6 2.2 3.4 3.5 +0.1 n (range) = 97 50 122 70 32-42 29-38 26-39 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among tech-led suppliers, marketplaces for sample (74%), software or tools (54%), and talent (46%) are the most-used “other” methods; use of crowdsourcing increased from 23% to 36% and talent marketplaces increased from 35% to 46% while prediction markets fell from 34% to 21%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 500+ FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Sample marketplaces 45% 23% 6% 16% 11% Research gamification 21% 27% 19% 33% 0% Software or tools marketplaces 33% 21% 13% 22% 12% Semiotics/cultural decoding 6% 38% 19% 25% 11% Prediction markets 9% 34% 19% 20% 18% Crowdsourcing 17% 24% 18% 37% 4% Behavioral economics models 14% 30% 15% 29% 12% Talent marketplaces 14% 31% 10% 29% 16% VR/AR/XR for research 12% 14% 27% 44% 3% n (range) = 32-55 Takeaway: Among service-led suppliers with 500+ FTE, the “other” method with the most potential is VR/AR/XR for research (only 49% who will probably use it currently do); each other method is at least 69% saturated. Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Marketplaces 37% 32% 50% 47% 70% -- -- -- Sample marketplaces -- -- -- -- -- 61% 68% +7% Software or tools marketplaces -- -- -- -- -- 46% 54% +8% Talent marketplaces -- -- -- -- -- 38% 45% +7% Research gamification 44% 31% 38% 42% 40% 57% 48% -9% Crowdsourcing 28% 16% 21% 33% 38% 28% 41% +13% Behavioral economics models 46% 29% 45% 52% 44% 51% 44% -7% Semiotics/cultural decoding -- -- -- -- -- -- 44% -- Prediction markets 27% 16% 23% 36% 48% 42% 43% +1% VR/AR/XR for research -- -- -- -- -- -- 26% -- AI or VR/AR/XR for CX/UX design 66% 44% 46% 34% 36% 57% -- -- VE/VR 33% 16% 19% 26% 25% 35% -- -- Average number used: 1.6 1.1 1.5 1.7 1.9 2.8 3.4 +0.6 n (range) = 106 85 117 97 45-71 59-68 32-55 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 500+ FTE, sample marketplaces (68%), software or tools marketplaces (54%), and research gamification (48%) are the three most-used “other” methods; use of crowdsourcing increased from 28% to 41%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 101-500 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Research gamification 14% 30% 27% 23% 5% Sample marketplaces 44% 19% 6% 14% 18% Semiotics/cultural decoding 11% 31% 18% 25% 15% Crowdsourcing 6% 22% 32% 35% 5% Prediction markets 11% 23% 21% 28% 18% Behavioral economics models 20% 25% 9% 22% 25% Talent marketplaces 13% 25% 7% 28% 27% Software or tools marketplaces 18% 18% 7% 22% 34% VR/AR/XR for research 0% 21% 22% 47% 10% n (range) = 33-56 Takeaway: Among service-led suppliers with 101-500 FTE, the “other” methods with the most potential are crowdsourcing (only 47% who will probably use it currently do) and VR/AR/XR for research (48%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Marketplaces 31% 30% 48% 35% 69% -- -- -- Sample marketplaces -- -- -- -- -- 72% 62% -10% Software or tools marketplaces -- -- -- -- -- 46% 36% -10% Talent marketplaces -- -- -- -- -- 35% 38% +3% Research gamification 30% 33% 34% 40% 31% 35% 45% +10% Behavioral economics models 41% 38% 31% 52% 48% 43% 44% +1% Semiotics/cultural decoding -- -- -- -- -- -- 42% -- Prediction markets 19% 25% 22% 40% 35% 30% 34% +4% Crowdsourcing 29% 15% 17% 20% 24% 16% 28% +12% VR/AR/XR for research -- -- -- -- -- -- 21% -- AI or VR/AR/XR for CX/UX design 71% 35% 36% 35% 39% 41% -- -- VE/VR 20% 13% 20% 18% 17% 11% -- -- Average number used: 2.4 1.9 2.1 2.4 2.6 3.3 3.5 +0.2 n (range) = 108 89 134 102 45-79 51-59 33-56 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 101-500 FTE, sample marketplaces (62%), research gamification (45%), and behavioral economics models (44%) are the three most-used “other” methods; use of crowdsourcing increased from 16% to 28%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: 21-100 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Sample marketplaces 48% 20% 5% 17% 10% Research gamification 14% 21% 31% 27% 7% Software or tools marketplaces 26% 27% 8% 23% 15% Behavioral economics models 24% 15% 16% 34% 11% Semiotics/cultural decoding 13% 5% 35% 35% 13% Crowdsourcing 13% 16% 17% 49% 5% Prediction markets 11% 10% 25% 40% 14% Talent marketplaces 21% 12% 12% 37% 19% VR/AR/XR for research 13% 15% 14% 53% 5% n (range) = 44-79 Takeaway: Among service-led suppliers with 21-100 FTE, the “other” methods with the most potential are semiotics/cultural decoding (only 33% who will probably use it currently do) and prediction markets (46%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Marketplaces 23% 32% 39% 48% 70% -- -- -- Sample marketplaces -- -- -- -- -- 66% 68% +2% Software or tools marketplaces -- -- -- -- -- 47% 54% +7% Talent marketplaces -- -- -- -- -- 37% 32% -5% Behavioral economics models 35% 37% 35% 49% 41% 42% 38% -4% Research gamification 26% 30% 30% 38% 35% 35% 35% -- Crowdsourcing 17% 15% 16% 21% 19% 13% 29% +16% VR/AR/XR for research -- -- -- -- -- -- 28% -- AI or VR/AR/XR for CX/UX design 54% 31% 35% 30% 28% 29% -- -- VE/VR 15% 13% 18% 14% 21% 11% -- -- Prediction markets 17% 24% 16% 37% 32% 29% 21% -8% Semiotics/cultural decoding -- -- -- -- -- -- 17% -- Average number used: 1.9 1.8 1.9 2.4 2.4 3.1 3.2 +0.1 n (range) = 169 130 142 184 62-112 79-100 44-79 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with 21-100 FTE, sample marketplaces (68%), software or tools marketplaces (54%), and behavioral economics models (38%) are the three most-used “other” methods, and behavioral economics models have been there each year; use of crowdsourcing increased from 13% to 29%. Source: GRIT 2026 Insights Practice Report, Greenbook. INTENTION/ATTITUDE TOWARD METHOD OR APPROACH (SERVICE-LED: ≤20 FTE) Use regularly Use occasionally Probably will use Unlikely to use Not familiar Sample marketplaces 39% 20% 10% 20% 10% Software or tools marketplaces 27% 27% 11% 20% 16% Behavioral economics models 12% 18% 19% 34% 17% Research gamification 7% 14% 26% 50% 3% Crowdsourcing 3% 19% 23% 43% 11% Talent marketplaces 11% 25% 8% 39% 17% Semiotics/cultural decoding 5% 20% 17% 44% 15% VR/AR/XR for research 5% 9% 22% 51% 12% Prediction markets 3% 13% 20% 54% 10% n (range) = 96-158 Takeaway: Among service-led suppliers with ≤20 FTE, the “other” methods with the most potential are VR/AR/XR for research (only 38% who will probably use it currently do), research gamification (44%), and prediction markets (44%). Source: GRIT 2026 Insights Practice Report, Greenbook USE OF METHODS/APPROACHES: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Marketplaces 14% 18% 22% 33% 44% -- -- -- Sample marketplaces -- -- -- -- -- 54% 59% +5% Software or tools marketplaces -- -- -- -- -- 45% 54% +9% Talent marketplaces -- -- -- -- -- 23% 36% +13% Behavioral economics models 28% 23% 30% 42% 29% 39% 30% -9% Semiotics/cultural decoding -- -- -- -- -- -- 25% -- Crowdsourcing 14% 12% 15% 17% 12% 10% 22% +12% Research gamification 20% 23% 23% 34% 28% 27% 21% -6% Prediction markets 15% 14% 15% 25% 23% 20% 16% -4% VR/AR/XR for research -- -- -- -- -- -- 14% -- AI or VR/AR/XR for CX/UX design 47% 20% 21% 22% 18% 17% -- -- VE/VR 5% 5% 9% 9% 3% 6% -- -- Average number used: 1.4 1.1 1.3 1.8 1.6 2.4 2.8 +0.4 n (range) = 310 221 234 271 77-142 136-155 96-158 Green shading indicates top three methodologies for that GRIT wave. Takeaway: Among service-led suppliers with ≤20 FTE, marketplaces for sample (59%), software or tools (54%), and talent (36%) are the most-used “other” methods; use of talent marketplaces increased from 23% to 36% and crowdsourcing increased from 10% to 22%. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC INTERPRETATION] This family divides into two groups. Marketplaces — for sample, software/tools, and increasingly talent — are the workhorses: top-three in nearly every segment, heavily and intensely used. They appear to serve different strategic functions by size: primary access infrastructure for smaller suppliers, a supplement to owned capability for larger ones. For brand-side analytics they may be transitional, since 66% of that segment expects automated/agentic systems to mediate most insights-services purchases (versus 37% of researchers) — a shift that would turn marketplaces from human browsing into machine-readable catalogs, and the segments expecting it most are the heaviest users today. The decision-science methods — behavioral economics models, research gamification, and prediction markets — cluster together and track segments with an analytical orientation; behavioral economics is the most embedded, gamification follows it up the curve with a lag, and prediction markets remain the most volatile. Newer entries such as semiotics/cultural decoding and VR/AR/XR show meaningful latent interest but low current adoption, with implementation cost and complexity, not unfamiliarity, the apparent barriers. Reported crowdsourcing gains likely combine a genuine return to its historical range with a labeling-change artifact. Across the family, brand-side analytics is again the most engaged, using 5.4 of nine methods on average versus 2.7 for researchers. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Managing Insights This section discusses current use of and attitudes toward agentic AI as it relates to the insights workflow. WHERE IS AGENTIC AI AND WHERE IS IT GOING? [ORIENTATION] CURRENT USE OF AGENTIC AI: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Analyzing or modeling data 62% 71% 76% 44% 43% 57% 59% Creating or updating reports, dashboards, or summaries 50% 71% 64% 44% 42% 71% 56% Preparing and integrating data 43% 73% 81% 35% 41% 57% 50% Monitoring for issues and alerts 29% 55% 48% 20% 21% 19% 25% Running surveys, interviews, or qualitative sessions 24% 30% 23% 19% 21% 16% 34% Recruiting, sampling, or routing participants 11% 30% 19% 13% 13% 19% 26% Selecting/shortlisting suppliers/partners for research/analytics 10% 29% 14% 9% 4% 3% 17% Average number of uses: 2.3 3.6 3.3 1.9 1.8 2.4 2.7 n = 88 77 20 80 36 29 29 Green shading indicates top three most-used methodologies. Takeaway: In each segment, the top three most frequent applications for agentic AI are analyzing or modeling data (ranging from 43% to 76%), creating or updating reports, dashboards, or summaries (42% to 71%), and preparing and integrating data (35% to 81%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Organizations that don’t leverage agentic AI will be left behind 57% 68% 71% 39% 57% 60% 70% Discussions about agentic AI dramatically overstate its adoption and impact 44% 59% 53% 54% 64% 49% 43% Automated/agentic systems will mediate most insights services purchases 37% 66% 43% 19% 31% 36% 50% Adoption of AI/agentic tools will force smaller, service-focused firms out 34% 51% 19% 20% 28% 31% 37% n = 88 77 20 80 36 29 29 Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Except for service-led suppliers with ≤20 FTE, most in each segment completely or mostly agree organizations that don’t leverage agentic AI will be left behind, and most in brand-side analytics (59%), tech-led suppliers (53%), service-led suppliers with ≤20 FTE (54%), and those with 21-100 FTE (64%) agree discussions about agentic AI dramatically overstate its adoption and impact. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. FORMAL ROLES IN AI/AUTOMATION POLICY [DATA] HAVE FORMAL ROLE IN DECISIONS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Suppliers or partners to work with 79% 72% 62% 83% 72% 59% 66% Technology, platforms, or tools to acquire 76% 85% 52% 75% 65% 48% 43% How much work is outsourced vs done in-house 65% 55% 47% 69% 47% 39% 38% Budgets for insights, analytics, and research 62% 67% 45% 69% 56% 40% 45% Which methods staff should learn and apply 61% 52% 47% 74% 58% 57% 58% Staffing or team structure 45% 59% 59% 75% 64% 61% 55% Policies for AI/automation and synthetic data 41% 65% 49% 72% 45% 40% 43% None of these 4% 0% 8% 2% 11% 20% 14% Average number of formal roles: 4.3 4.6 3.6 5.2 4.1 3.4 3.5 n = 176 152 39 158 79 56 55 Green shading indicates top three most frequent roles. Takeaway: Supplier/partner selection is among the top three formal decision-making roles in each segment, as is staffing or team structure in each supplier segment. Except for service-led suppliers with more than 100 FTE, deciding which technology, platforms, or tools to acquire is one of the top three roles. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. AGENTIC AI USE AND ATTITUDES | BRAND POV [DATA] HAVE FORMAL ROLE IN DECISIONS: BRAND SEGMENT Research Analytics Research - analytics Suppliers or partners to work with 79% 72% +7% Technology, platforms, or tools to acquire 76% 85% -9% How much work is outsourced vs done in-house 65% 55% +10% Budgets for insights, analytics, and research 62% 67% -5% Which methods staff should learn and apply 61% 52% +9% Staffing or team structure 45% 59% -14% Policies for AI/automation and synthetic data 41% 65% -24% None of these 4% 0% +4% Average number of formal roles: 4.3 4.6 -3% n = 176 152 Green shading indicates top three most-used methodologies. Takeaway: Brand-side researchers are more likely than analytics professionals to have a formal role in how much work is outsourced (65% to 55%), and analytics professionals are more likely to have a formal role in policies for AI/automation and synthetic data (65% to 41%) and staffing or team structure (59% to 45%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CURRENT USE OF AGENTIC AI: BRAND SEGMENT Research Analytics Research - analytics Analyzing or modeling data 62% 71% -9% Creating or updating reports, dashboards, or summaries 50% 71% -21% Preparing and integrating data 43% 73% -30% Monitoring for issues and alerts 29% 55% -26% Running surveys, interviews, or qualitative sessions 24% 30% -6% Recruiting, sampling, or routing participants 11% 30% -19% Selecting/shortlisting suppliers/partners for research/analytics 10% 29% -19% Average number of uses: 2.3 3.6 -1.3 n = 88 77 Green shading indicates top three most-used methodologies. Takeaway: Brand-side analytics professionals are substantially more likely than researchers to currently use agentic AI across all tasks, with the largest gaps in preparing and integrating data (73% vs. 43%) and monitoring for issues and alerts (55% vs. 29%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. CURRENT USE OF AGENTIC AI (BRAND: RESEARCH) Yes No Don’t Know Analyzing or modeling data 62% 31% 8% Creating or updating reports, dashboards, or summaries 50% 42% 8% Preparing and integrating data 43% 49% 8% Monitoring for issues and alerts 29% 55% 16% Running surveys, interviews, or qualitative sessions 24% 71% 5% Recruiting, sampling, or routing participants 11% 80% 9% Selecting/shortlisting suppliers/partners for research/analytics 10% 78% 12% n = 88 Takeaway: Brand-side researchers are most likely to report use of agentic AI for analyzing or modeling data (62%), creating or updating reports, dashboards, or summaries (50%), and preparing and integrating data (43%). Source: GRIT 2026 Insights Practice Report, Greenbook CURRENT USE OF AGENTIC AI (BRAND: ANALYTICS) Yes No Don’t Know Preparing and integrating data 73% 25% 1% Analyzing or modeling data 71% 29% 1% Creating or updating reports, dashboards, or summaries 71% 29% 1% Monitoring for issues and alerts 55% 41% 4% Recruiting, sampling, or routing participants 30% 64% 6% Running surveys, interviews, or qualitative sessions 30% 67% 4% Selecting/shortlisting suppliers/partners for research/analytics 29% 67% 4% n = 77 Takeaway: Brand-side analytics professionals are most likely to report use of agentic AI for preparing and integrating data (73%), analyzing or modeling data (71%), creating or updating reports, dashboards, or summaries (71%), and monitoring for issues and alerts (55%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE: BRAND SEGMENT Research Analytics Research - analytics Organizations that don’t leverage agentic AI will be left behind 57% 68% -11% Discussions about agentic AI dramatically overstate its adoption and impact 44% 59% -15% Automated/agentic systems will mediate most insights services purchases 37% 66% -29% Adoption of AI/agentic tools will force smaller, service-focused firms out 34% 51% -17% n = 88 77 Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Brand-side analytics professionals are more likely than researchers to completely or mostly agree automated/agentic systems will mediate most insights services purchases (66% to 37%) and adoption of AI/agentic tools will force smaller, service-focused firms out of the market (51% to 34%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (BRAND: RESEARCH) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Organizations that don’t leverage agentic AI will be left behind 26% 31% 30% 7% 6% Discussions about agentic AI dramatically overstate its adoption and impact 17% 28% 28% 20% 8% Automated/agentic systems will mediate most insights services purchases 13% 25% 33% 19% 10% Adoption of AI/agentic tools will force smaller, service-focused firms out 6% 28% 30% 26% 10% n = 88 Takeaway: Most brand-side researchers completely or mostly agree organizations that don’t leverage agentic AI will be left behind (57%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (BRAND: ANALYTICS) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Organizations that don’t leverage agentic AI will be left behind 37% 31% 25% 4% 3% Automated/agentic systems will mediate most insights services purchases 13% 54% 28% 4% 1% Discussions about agentic AI dramatically overstate its adoption and impact 20% 38% 32% 6% 3% Adoption of AI/agentic tools will force smaller, service-focused firms out 21% 29% 35% 11% 3% n = 77 Takeaway: Most brand-side analytics professionals completely or mostly agree organizations that don’t leverage agentic AI will be left behind (68%), automated/agentic systems will mediate most insights services purchases (67%), and discussions about agentic AI dramatically overstate its adoption and impact (58%). Source: GRIT 2026 Insights Practice Report, Greenbook AGENTIC AI USE AND ATTITUDES | SUPPLIER POV [DATA] HAVE FORMAL ROLE IN DECISIONS: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Suppliers or partners to work with 62% 83% 72% 59% 66% Which methods staff should learn and apply 47% 74% 58% 57% 58% Staffing or team structure 59% 75% 64% 61% 55% Budgets for insights, analytics, and research 45% 69% 56% 40% 45% Policies for AI/automation and synthetic data 49% 72% 45% 40% 43% Technology, platforms, or tools to acquire 52% 75% 65% 48% 43% How much work is outsourced vs done in-house 47% 69% 47% 39% 38% None of these 8% 2% 11% 20% 14% Average number of formal roles: 3.6 5.2 4.1 3.4 3.5 n = 39 158 79 56 55 Green shading indicates top three most frequent roles. Takeaway: Across supplier segments, the top three formal decision roles include selecting suppliers and partners and staffing or team structure. For service-led suppliers with more than 100 FTE, deciding which methods staff should learn and apply is in the top three, while deciding which technology, platforms, or tools to acquire is in the top three in each other segment. Source: GRIT 2026 Insights Practice Report, Greenbook. CURRENT USE OF AGENTIC AI: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Analyzing or modeling data 76% 44% 43% 57% 59% Creating or updating reports, dashboards, or summaries 64% 44% 42% 71% 56% Preparing and integrating data 81% 35% 41% 57% 50% Running surveys, interviews, or qualitative sessions 23% 19% 21% 16% 34% Recruiting, sampling, or routing participants 19% 13% 13% 19% 26% Monitoring for issues and alerts 48% 20% 21% 19% 25% Selecting/shortlisting suppliers/partners for research/analytics 14% 9% 4% 3% 17% Average number of uses: 3.3 1.9 1.8 2.4 2.7 n = 20 80 36 29 29 Green shading indicates top three most frequent uses. Takeaway: The top three current uses for agentic AI are the same in each segment: analyzing or modeling data (ranging from 43% to 76%), creating or updating reports, dashboards, or summaries (42% to 71%), and preparing and integrating data (35% to 81%). Source: GRIT 2026 Insights Practice Report, Greenbook. ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Organizations that don’t leverage agentic AI will be left behind 71% 39% 57% 60% 70% Automated/agentic systems will mediate most insights services purchases 43% 19% 31% 36% 50% Discussions about agentic AI dramatically overstate its adoption and impact 53% 54% 64% 49% 43% Adoption of AI/agentic tools will force smaller, service-focused firms out 19% 20% 28% 31% 37% n = 20 80 36 29 29 Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Except for service-led suppliers with ≤20 FTE (39%), the majority in each segment completely or mostly agree organizations that don’t leverage agentic AI will be left behind, from 57% of service-led with 21-100 FTE to 71% of tech-led; most tech-led (53%) and service-led suppliers with ≤20 FTE (54%) and 21-100 FTE (64%) completely or mostly agree discussions about agentic AI dramatically overstate its adoption and impact. Source: GRIT 2026 Insights Practice Report, Greenbook. AGENTIC AI USE AND ATTITUDES | TECH-LED POV [DATA] CURRENT USE OF AGENTIC AI (TECH-LED) Yes No Don’t Know Preparing and integrating data 81% 19% 0% Analyzing or modeling data 76% 24% 0% Creating or updating reports, dashboards, or summaries 64% 36% 0% Monitoring for issues and alerts 48% 48% 4% Running surveys, interviews, or qualitative sessions 23% 77% 0% Recruiting, sampling, or routing participants 19% 63% 18% Selecting/shortlisting suppliers/partners for research/analytics 14% 74% 12% n = 20 Takeaway: Tech-led suppliers are most likely to report use of agentic AI for preparing and integrating data (81%), analyzing or modeling data (76%), and creating or updating reports, dashboards, or summaries (64%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (TECH-LED) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Organizations that don’t leverage agentic AI will be left behind 31% 40% 18% 3% 8% Discussions about agentic AI dramatically overstate its adoption and impact 22% 31% 34% 13% 0% Automated/agentic systems will mediate most insights services purchases 20% 23% 23% 27% 8% Adoption of AI/agentic tools will force smaller, service-focused firms out 19% 0% 37% 22% 22% n = 20 Takeaway: Most tech-led suppliers completely or mostly agree organizations that don’t leverage agentic AI will be left behind (71%) and discussions about agentic AI dramatically overstate its adoption and impact (53%). Source: GRIT 2026 Insights Practice Report, Greenbook CURRENT USE OF AGENTIC AI (SERVICE-LED: 500+ FTE) Yes No Don’t Know Analyzing or modeling data 59% 32% 8% Creating or updating reports, dashboards, or summaries 56% 41% 3% Preparing and integrating data 50% 47% 3% Running surveys, interviews, or qualitative sessions 34% 58% 8% Recruiting, sampling, or routing participants 26% 48% 26% Monitoring for issues and alerts 25% 43% 32% Selecting/shortlisting suppliers/partners for research/analytics 17% 49% 34% n = 29 Takeaway: Service-led suppliers with 500+ FTE are most likely to report use of agentic AI for analyzing or modeling data (59%), creating or updating reports, dashboards, or summaries (56%), and preparing and integrating data (50%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (SERVICE-LED: 500+ FTE) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Organizations that don’t leverage agentic AI will be left behind 31% 39% 28% 3% 0% Automated/agentic systems will mediate most insights services purchases 15% 35% 22% 17% 11% Discussions about agentic AI dramatically overstate its adoption and impact 24% 19% 27% 24% 6% Adoption of AI/agentic tools will force smaller, service-focused firms out 23% 14% 31% 21% 10% n = 29 Takeaway: At least half of service-led suppliers with 500+ FTE completely or mostly agree organizations that don’t leverage agentic AI will be left behind (70%) and automated/agentic systems will mediate most insights services purchases (50%). Source: GRIT 2026 Insights Practice Report, Greenbook CURRENT USE OF AGENTIC AI (SERVICE-LED: 101-500 FTE) Yes No Don’t Know Creating or updating reports, dashboards, or summaries 71% 23% 6% Analyzing or modeling data 57% 26% 17% Preparing and integrating data 57% 26% 17% Monitoring for issues and alerts 19% 66% 15% Recruiting, sampling, or routing participants 19% 75% 6% Running surveys, interviews, or qualitative sessions 16% 74% 10% Selecting/shortlisting suppliers/partners for research/analytics 3% 82% 15% n = 29 Takeaway: Service-led suppliers with 101-500 FTE are most likely to report use of agentic AI for creating or updating reports, dashboards, or summaries (71%), analyzing or modeling data (57%), and preparing and integrating data (57%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (SERVICE-LED: 101-500 FTE) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Organizations that don’t leverage agentic AI will be left behind 21% 39% 19% 22% 0% Discussions about agentic AI dramatically overstate its adoption and impact 10% 40% 51% 0% 0% Automated/agentic systems will mediate most insights services purchases 9% 27% 35% 23% 6% Adoption of AI/agentic tools will force smaller, service-focused firms out 11% 19% 20% 35% 14% n = 29 Takeaway: At least half of service-led suppliers with 101-500 FTE completely or mostly agree organizations that don’t leverage agentic AI will be left behind (60%) and discussions about agentic AI dramatically overstate its adoption and impact (50%). Source: GRIT 2026 Insights Practice Report, Greenbook CURRENT USE OF AGENTIC AI (SERVICE-LED: 21-100 FTE) Yes No Don’t Know Analyzing or modeling data 43% 53% 4% Creating or updating reports, dashboards, or summaries 42% 51% 7% Preparing and integrating data 41% 57% 2% Monitoring for issues and alerts 21% 75% 4% Running surveys, interviews, or qualitative sessions 21% 72% 7% Recruiting, sampling, or routing participants 13% 75% 13% Selecting/shortlisting suppliers/partners for research/analytics 4% 90% 5% n = 36 Takeaway: Service-led suppliers with 21-500 FTE are most likely to report use of agentic AI for analyzing or modeling data (43%), creating or updating reports, dashboards, or summaries (42%), and preparing and integrating data (41%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (SERVICE-LED: 21-100 FTE) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Discussions about agentic AI dramatically overstate its adoption and impact 20% 44% 31% 5% 0% Organizations that don’t leverage agentic AI will be left behind 14% 43% 29% 9% 5% Automated/agentic systems will mediate most insights services purchases 17% 14% 41% 25% 3% Adoption of AI/agentic tools will force smaller, service-focused firms out 6% 22% 40% 23% 9% n = 36 Takeaway: Most service-led suppliers with 21-100 FTE completely or mostly agree discussions about agentic AI dramatically overstate its adoption and impact (64%) and organizations that don’t leverage agentic AI will be left behind (57%). Source: GRIT 2026 Insights Practice Report, Greenbook CURRENT USE OF AGENTIC AI (SERVICE-LED: ≤20 FTE) Yes No Don’t Know Analyzing or modeling data 44% 56% 0% Creating or updating reports, dashboards, or summaries 44% 55% 1% Preparing and integrating data 35% 65% 0% Monitoring for issues and alerts 20% 80% 0% Recruiting, sampling, or routing participants 13% 83% 3% Running surveys, interviews, or qualitative sessions 19% 79% 1% Selecting/shortlisting suppliers/partners for research/analytics 9% 86% 4% n = 80 Takeaway: Service-led suppliers with ≤20 FTE are most likely to report use of agentic AI for analyzing or modeling data (44%), creating or updating reports, dashboards, or summaries (44%), and preparing and integrating data (35%). Source: GRIT 2026 Insights Practice Report, Greenbook ATTITUDES TOWARD AGENTIC AI - COMPLETELY/MOSTLY AGREE (SERVICE-LED: ≤20 FTE) Completely agree Mostly agree Somewhat agree Agree very little Don’t agree at all Discussions about agentic AI dramatically overstate its adoption and impact 18% 35% 20% 19% 8% Organizations that don’t leverage agentic AI will be left behind 20% 19% 44% 14% 3% Adoption of AI/agentic tools will force smaller, service-focused firms out 8% 12% 37% 29% 14% Automated/agentic systems will mediate most insights services purchases 11% 8% 42% 27% 12% n = 80 Takeaway: Most service-led suppliers with ≤20 FTE completely or mostly agree discussions about agentic AI dramatically overstate its adoption and impact (53%). Source: GRIT 2026 Insights Practice Report, Greenbook THE BIG PICTURE [STRATEGIC INTERPRETATION] Agentic AI has arrived in the insights workflow, and every segment has converged on the same three applications regardless of adoption rate: analyzing or modeling data, creating or updating reports, and preparing or integrating data. It is being deployed where mistakes are recoverable and withheld where they are not — supplier selection (3%–29% across segments) and recruiting and sampling (11%–30%) remain the least common uses. That may not last: 66% of brand-side analytics professionals agree automated/agentic systems will eventually mediate most insights-services purchases, with agreement next-highest among the largest suppliers and declining as supplier size falls. Most segments also agree that agentic AI’s impact is overstated, but the agreement means different things — among brand analytics, 59% call it overstated while using it for 3.6 of seven tasks and believing organizations will fall behind without it, whereas the smallest suppliers call it overstated while using fewer than two. A governance gap runs through the section: AI/automation policy is the only formal decision role that fails to reach the top three in any segment, even among the heaviest users. Insights professionals are enabling agentic AI through adjacent formal roles without formally governing it — a gap sharpest among brand-side researchers, who rank AI policy last (41%) despite 79% claiming authority over supplier selection, the activity their analytics colleagues most expect agentic systems to mediate. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Investing in Insights This section looks at trends in automation and outsourcing and whether GRIT participants think their organizations rely on them too much, too little, or the right amount. WHO NEEDS MORE AUTOMATION? [ORIENTATION] HOW MUCH ORGANIZATION RELIES ON AUTOMATION - FAR/A BIT TOO LITTLE: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Analyzing and modeling insights 57% 20% 31% 41% 33% 55% 59% Preparing and integrating data 53% 30% 45% 37% 47% 49% 54% Designing research and analytics 53% 41% 26% 33% 40% 53% 46% Communicating and activating insights 53% 44% 31% 26% 35% 41% 43% Sourcing participants and data 50% 54% 30% 44% 48% 54% 46% Executing fieldwork and data collection 45% 37% 64% 38% 52% 64% 40% n (range) = 67-81 72-76 16-20 64-77 30-33 26-37 20-27 “No opinion” removed. Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: At least half of brand-side researchers believe automation is under-utilized for five tasks, from 50% for sourcing participants and data to 57% for analyzing and modeling insights; most tech-led suppliers and larger service-led suppliers also have unmet needs for automation. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. HOW MUCH ORGANIZATION RELIES ON OUTSOURCING - FAR/A BIT TOO LITTLE: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Preparing and integrating data 21% 34% 14% 7% 25% 18% 34% Designing research and analytics 19% 23% 6% 9% 24% 22% 31% Analyzing and modeling insights 18% 26% 5% 14% 25% 12% 34% Communicating and activating insights 15% 30% 0% 16% 23% 19% 33% Sourcing participants and data 14% 27% 6% 9% 23% 6% 32% Executing fieldwork and data collection 11% 26% 11% 7% 12% 4% 15% n (range) = 84-87 74-75 17-19 75-78 31-33 26-28 24-26 “No opinion” removed. Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Beliefs that outsourcing is under-utilized never exceed about one-third of any segment for any task; the need for more outsourcing is strongest among service-led suppliers with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. AUTOMATION AND OUTSOURCING | BRAND POV [DATA] HOW MUCH ORGANIZATION RELIES ON AUTOMATION - FAR/A BIT TOO MUCH: BRAND SEGMENT Research Analytics Research - analytics Analyzing and modeling insights 13% 25% -12% Preparing and integrating data 5% 19% -14% Communicating and activating insights 5% 21% -16% Designing research and analytics 5% 11% -6% Executing fieldwork and data collection 3% 19% -16% Sourcing participants and data 2% 13% -11% n (range) = 67-81 72-76 “No opinion” has been removed. Takeaway: Although not very likely to believe their organization relies too much on automation for any task, brand-side analytics professionals are consistently more likely than researchers to believe it across every task; the largest gaps are in communicating/activating insights (21% vs. 5%) and executing fieldwork (19% vs. 3%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. HOW MUCH ORGANIZATION RELIES ON AUTOMATION - FAR/A BIT TOO LITTLE: BRAND SEGMENT Research Analytics Research - analytics Analyzing and modeling insights 57% 20% +37% Communicating and activating insights 53% 44% +9% Designing research and analytics 53% 41% +12% Preparing and integrating data 53% 30% +23% Sourcing participants and data 50% 54% -4% Executing fieldwork and data collection 45% 37% +8% n (range) = 67-81 72-76 No opinion removed. Takeaway: Brand-side researchers are more likely than analytics professionals to believe their organizations do not use automation enough for analyzing and modeling insights (57% to 20%) and preparing and integrating data (53% to 30%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. HOW MUCH ORGANIZATION RELIES ON AUTOMATION (BRAND: RESEARCH) Far too much A bit too much Right amount A bit too little Far too little No opinion Analyzing and modeling insights 3% 9% 28% 42% 9% 9% Preparing and integrating data 1% 4% 39% 41% 7% 8% Communicating and activating insights 0% 5% 38% 38% 10% 9% Designing research and analytics 0% 4% 37% 34% 11% 14% Executing fieldwork and data collection 0% 2% 40% 25% 10% 22% Sourcing participants and data 0% 1% 35% 20% 16% 27% n = 88 Takeaway: Most brand-side researchers believe their organization relies too little on automation for analyzing and modeling insights (51%), and nearly half say the same about preparing and integrating data (48%) and communicating and activating insights (48%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON AUTOMATION (BRAND: ANALYTICS) Far too much A bit too much Right amount A bit too little Far too little No opinion Analyzing and modeling insights 1% 23% 53% 14% 5% 3% Communicating and activating insights 4% 16% 34% 26% 17% 2% Preparing and integrating data 3% 15% 49% 22% 7% 3% Executing fieldwork and data collection 2% 16% 42% 25% 10% 4% Sourcing participants and data 2% 10% 30% 37% 13% 8% Designing research and analytics 1% 10% 47% 34% 6% 2% n = 77 Takeaway: Across all activities, brand-side analytics professionals are more likely believe their organization relies too little on automation than too much, except for analyzing and modeling insights (19% to 24%); the biggest gaps are sourcing participants and data (50% too little to 12% too much), designing research and analytics (40% to 11%), and communicating and activating insights (43% to 20%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW ORGANIZATION’S USE OF AUTOMATION WILL CHANGE: BRAND SEGMENT Increase significantly Increase slightly Stay about the same Decrease slightly Decrease significantly Research (n = 176) 36% 52% 12% 0% 0% Analytics (n = 152) 49% 43% 8% 0% 0% Takeaway: Virtually all brand-side professionals expect automation use to increase: 88% of researchers and 92% of analytics anticipate some increase; analytics professionals are more likely say it will increase significantly (49% to 35%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING - FAR/A BIT TOO MUCH: BRAND SEGMENT Research Analytics Research - analytics Sourcing participants and data 12% 36% -24% Executing fieldwork and data collection 10% 31% -21% Analyzing and modeling insights 10% 20% -10% Designing research and analytics 10% 23% -13% Preparing and integrating data 9% 21% -12% Communicating and activating insights 9% 19% -10% n (range) = 84-87 74-75 “No opinion” removed. Takeaway: Although not very likely to believe their organization relies too much on outsourcing, brand-side analytics professionals are consistently more likely than researchers to believe that across all tasks; the largest gaps are in sourcing participants and data (36% vs. 12%) and executing fieldwork (31% vs. 10%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. HOW MUCH ORGANIZATION RELIES ON OUTSOURCING - FAR/A BIT TOO LITTLE: BRAND SEGMENT Research Analytics Research - analytics Preparing and integrating data 21% 34% -13% Designing research and analytics 19% 23% -4% Analyzing and modeling insights 18% 26% -8% Communicating and activating insights 15% 30% -15% Sourcing participants and data 14% 27% -13% Executing fieldwork and data collection 11% 26% -15% n (range) = 84-87 74-75 No opinion removed. Takeaway: Although not very likely to believe their organization relies too little on outsourcing, brand-side analytics professionals are consistently more likely than researchers to believe that across all tasks; the largest gaps are in executing fieldwork and data collection (26% vs. 11%) and communicating and activating insights (30% vs. 15%). Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (BRAND: RESEARCH) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 0% 11% 72% 13% 1% 3% Designing research and analytics 1% 9% 70% 10% 8% 1% Executing fieldwork and data collection 1% 8% 76% 7% 3% 4% Analyzing and modeling insights 4% 5% 67% 14% 2% 7% Preparing and integrating data 2% 7% 68% 16% 5% 2% Communicating and activating insights 0% 9% 75% 8% 7% 2% n = 88 Takeaway: At least two-thirds of brand-side researchers believe their organization relies the right amount on outsourcing for any tasks, from 67% for analyzing and modeling insights to 76% for executing fieldwork and data collection. Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (BRAND: ANALYTICS) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 7% 28% 36% 23% 2% 4% Executing fieldwork and data collection 5% 25% 41% 19% 6% 4% Designing research and analytics 4% 17% 52% 18% 3% 5% Preparing and integrating data 3% 17% 43% 27% 6% 3% Analyzing and modeling insights 5% 14% 53% 19% 6% 3% Communicating and activating insights 4% 14% 49% 23% 5% 5% n = 77 Takeaway: Brand-side analytics professionals’ views on outsourcing are mixed; about half think they rely on the right amount for analyzing and modeling insights (53%), designing research and analytics (52%), and communicating and activating insights (49%), but other views split across too much versus too little. Source: GRIT 2026 Insights Practice Report, Greenbook HOW ORGANIZATION’S USE OF OUTSOURCING WILL CHANGE: BRAND SEGMENT AUTOMATION AND OUTSOURCING | SUPPLIER POV [DATA] HOW MUCH ORGANIZATION RELIES ON AUTOMATION - FAR/A BIT TOO MUCH: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Communicating and activating insights 0% 3% 10% 3% 26% Designing research and analytics 0% 3% 7% 3% 19% Sourcing participants and data 5% 4% 7% 2% 14% Executing fieldwork and data collection 5% 5% 9% 2% 14% Preparing and integrating data 5% 6% 11% 3% 10% Analyzing and modeling insights 0% 4% 12% 2% 2% n = 16-20 64-77 30-33 26-37 20-27 “No opinion” removed. Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Although not very likely to believe their organization relies too much on automation, concerns peak with service-led suppliers with 500+ FTE for communicating/activating insights (26%) and designing research and analytics (19%). Source: GRIT 2026 Insights Practice Report, Greenbook. HOW MUCH ORGANIZATION RELIES ON AUTOMATION - FAR/A BIT TOO LITTLE (SUPPLIER) Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Analyzing and modeling insights 31% 41% 33% 55% 59% Preparing and integrating data 45% 37% 47% 49% 54% Sourcing participants and data 30% 44% 48% 54% 46% Designing research and analytics 26% 33% 40% 53% 46% Communicating and activating insights 31% 26% 35% 41% 43% Executing fieldwork and data collection 64% 38% 52% 64% 40% n = 16-20 64-77 30-33 26-37 20-27 “No opinion” removed. Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Most in three supplier segments believe too little automation is used in executing fieldwork and data collection; nearly half or more in the service-led supplier segments with more than 100 FTE believe it is not use enough for analyzing and modeling insights, preparing and integrating data, sourcing participants and data, and designing research and analytics. Source: GRIT 2026 Insights Practice Report, Greenbook. HOW ORGANIZATION’S USE OF AUTOMATION WILL CHANGE: SUPPLIER SEGMENT Increase significantly Increase slightly Stay about the same Decrease slightly Decrease significantly Tech-led (n = 39) 51% 37% 13% 0% 0% Service-led: 500+ FTE (n = 55) 60% 33% 7% 0% 0% Service-led: 101-500 FTE (n = 55) 68% 28% 7% 0% 0% Service-led: 21-100 FTE (n = 79) 59% 35% 5% 0% 0% Service-led: ≤20 FTE (n = 156) 37% 51% 12% 0% 0% Takeaway: Except for service-led suppliers with ≤20 FTE suppliers (37%), most suppliers in each segment expect their organization’s use of automation to increase significantly, from 51% for tech-led to 66% for service-led with 101-500 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING - FAR/A BIT TOO MUCH: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Executing fieldwork and data collection 6% 5% 23% 7% 19% Sourcing participants and data 0% 11% 26% 18% 16% Analyzing and modeling insights 0% 10% 7% 3% 11% Communicating and activating insights 5% 5% 12% 3% 11% Designing research and analytics 0% 6% 8% 3% 10% Preparing and integrating data 5% 8% 10% 3% 8% n (range) = 17-19 75-78 31-33 26-28 24-26 “No opinion” removed. Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Although not very likely to believe their organization relies too much on outsourcing, concerns peak with service-led suppliers with 21-100+ FTE for sourcing participants and data (26%) and executing fieldwork and data collection (23%). Source: GRIT 2026 Insights Practice Report, Greenbook. HOW MUCH ORGANIZATION RELIES ON OUTSOURCING - FAR/A BIT TOO LITTLE (SUPPLIER) Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Preparing and integrating data 14% 7% 25% 18% 34% Analyzing and modeling insights 5% 14% 25% 12% 34% Communicating and activating insights 0% 16% 23% 19% 33% Sourcing participants and data 6% 9% 23% 6% 32% Designing research and analytics 6% 9% 24% 22% 31% Executing fieldwork and data collection 11% 7% 12% 4% 15% n (range) = 17-19 75-78 31-33 26-28 24-26 “No opinion” removed. Green indicates relatively higher agreement; red indicates relatively lower agreement. Color scale applies across both segments. Takeaway: Among service-led suppliers with 500+ FTE, about one-third believe they do not use outsourcing enough for preparing and integrating data (34%), analyzing and modeling insights (34%), communicating and activating insights (33%), sourcing participants and data (32%), and designing research and analytics (31%). Source: GRIT 2026 Insights Practice Report, Greenbook. HOW ORGANIZATION’S USE OF OUTSOURCING WILL CHANGE: SUPPLIER SEGMENT Increase significantly Increase slightly Stay about the same Decrease slightly Decrease significantly Tech-led (n = 39) 7% 17% 66% 11% 0% Service-led: 500+ FTE (n = 55) 6% 27% 47% 18% 2% Service-led: 101-500 FTE (n = 56) 0% 24% 60% 15% 2% Service-led: 21-100 FTE (n = 79) 9% 20% 58% 8% 5% Service-led: ≤20 FTE (n = 158) 7% 19% 64% 8% 2% Takeaway: Except for service-led suppliers with 500+ FTE suppliers (47%), most suppliers in each segment expect their organization’s use of outsourcing to stay the same; in each segment, the percentages expecting increases outnumber those expecting decreases. Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON AUTOMATION (TECH-LED) Far too much A bit too much Right amount A bit too little Far too little No opinion Analyzing and modeling insights 5% 0% 64% 16% 15% 0% Designing research and analytics 5% 0% 62% 15% 8% 10% Preparing and integrating data 5% 0% 50% 30% 15% 0% Communicating and activating insights 0% 0% 69% 16% 15% 0% Sourcing participants and data 0% 0% 52% 15% 8% 25% Executing fieldwork and data collection 0% 0% 29% 37% 15% 19% n = 20 Takeaway: Except for executing fieldwork and data collection (29%), at least half of tech-led suppliers believe their company uses the right amount of automation; however, more than 20% believe they use too little across activities, led by preparing and integrating data (45%) and executing fieldwork and data collection (52%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (TECH-LED) Far too much A bit too much Right amount A bit too little Far too little No opinion Communicating and activating insights 0% 5% 91% 0% 0% 4% Preparing and integrating data 0% 5% 78% 9% 5% 4% Executing fieldwork and data collection 0% 5% 72% 10% 0% 14% Analyzing and modeling insights 0% 0% 91% 0% 5% 4% Designing research and analytics 0% 0% 76% 0% 5% 19% Sourcing participants and data 0% 0% 76% 0% 5% 19% n = 20 Takeaway: Across activities, more than 70% of tech-led suppliers believe they use the right amount of outsourcing, led by communicating and activating insights (91%) and analyzing and modeling insights (91%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON AUTOMATION (SERVICE-LED: 500+ FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 6% 12% 19% 16% 16% 32% Executing fieldwork and data collection 6% 9% 33% 21% 11% 20% Analyzing and modeling insights 4% 8% 24% 37% 16% 11% Preparing and integrating data 6% 7% 29% 29% 20% 10% Designing research and analytics 4% 5% 41% 29% 13% 7% Communicating and activating insights 2% 0% 49% 31% 8% 9% n = 29 Takeaway: Service-led suppliers with 500+ FTE are more likely to believe their organizations use too little automation rather than too much, especially for analyzing and modeling insights (53%) and preparing and integrating data (49%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (SERVICE-LED: 500+ FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Executing fieldwork and data collection 16% 0% 53% 5% 7% 19% Sourcing participants and data 14% 0% 46% 12% 15% 13% Communicating and activating insights 0% 9% 49% 9% 20% 13% Analyzing and modeling insights 0% 9% 48% 5% 24% 13% Designing research and analytics 2% 7% 53% 4% 23% 11% Preparing and integrating data 0% 7% 52% 10% 20% 11% n = 29 Takeaway: Across activities, about half of service-led suppliers with 500+ FTE believe they use the right amount of outsourcing, but those who think they use too little outnumber those who think they use too much for all but executing fieldwork and data collection (12% to 16%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON AUTOMATION (SERVICE-LED: 101-500 FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 2% 0% 40% 20% 29% 9% Communicating and activating insights 2% 0% 53% 36% 3% 6% Preparing and integrating data 2% 0% 46% 44% 3% 6% Analyzing and modeling insights 2% 0% 40% 52% 0% 6% Designing research and analytics 0% 2% 40% 41% 6% 11% Executing fieldwork and data collection 2% 0% 31% 41% 17% 9% n = 29 Takeaway: Service-led suppliers with 101-500 FTE are more likely to believe their organizations use too little automation rather than too much, especially for analyzing and modeling insights (52% to 2%), sourcing participants and data (49% to 2%), executing fieldwork and data collection (58% to 2%), designing research and analytics (47% to 2%), and preparing and integrating data (47% to 2%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (SERVICE-LED: 101-500 FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 4% 14% 74% 6% 0% 3% Executing fieldwork and data collection 0% 7% 84% 4% 0% 6% Analyzing and modeling insights 0% 3% 78% 8% 3% 9% Preparing and integrating data 0% 3% 72% 13% 3% 9% Communicating and activating insights 0% 3% 71% 14% 3% 9% Designing research and analytics 0% 3% 69% 16% 3% 9% n = 29 Takeaway: Across activities, more than two-thirds of service-led suppliers with 101-500 FTE believe they use the right amount of outsourcing, but those who think they use too little outnumber those who think they use too much for analyzing and modeling insights (11% to 3%), preparing and integrating data (16% to 3%), communicating and activating insights (17% to 3%), and designing research and analytics (19% to 3%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON AUTOMATION (SERVICE-LED: 21-100 FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Communicating and activating insights 0% 11% 50% 26% 6% 7% Designing research and analytics 0% 11% 45% 35% 2% 7% Preparing and integrating data 0% 8% 40% 33% 9% 10% Sourcing participants and data 0% 8% 35% 22% 18% 17% Analyzing and modeling insights 6% 0% 56% 26% 4% 7% Executing fieldwork and data collection 6% 0% 35% 26% 19% 15% n = 36 Takeaway: Across all activities, service-led suppliers with 21-100 FTE are more likely to believe their organizations use too little automation rather than too much, especially for executing fieldwork and data collection (45% to 6%), preparing and integrating data (42% to 8%), and sourcing participants and data (40% to 8%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (SERVICE-LED: 21-100 FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 12% 10% 43% 13% 6% 16% Executing fieldwork and data collection 3% 17% 56% 11% 0% 13% Communicating and activating insights 6% 4% 55% 8% 12% 15% Preparing and integrating data 2% 6% 56% 9% 12% 15% Analyzing and modeling insights 6% 0% 57% 12% 10% 15% Designing research and analytics 0% 6% 56% 8% 12% 17% n = 36 Takeaway: Across all activities except sourcing participants and data (43%), most service-led suppliers with 21-100 FTE believe they use the right amount of outsourcing, but those who think they use too much outnumber those who think they use too little for sourcing participants and data (22% to 19%) and executing fieldwork and data collection (22% to 11%); across the remaining activities, those who think they use too little outnumber those who think they use too much. Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON AUTOMATION (SERVICE-LED: ≤20 FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Designing research and analytics 1% 4% 57% 24% 7% 7% Preparing and integrating data 1% 4% 54% 27% 9% 6% Analyzing and modeling insights 0% 4% 53% 33% 6% 4% Communicating and activating insights 1% 2% 66% 19% 5% 7% Sourcing participants and data 1% 1% 42% 21% 14% 21% Executing fieldwork and data collection 1% 1% 52% 22% 11% 14% n = 80 Takeaway: Across all activities except sourcing participants and data (42%), most service-led suppliers with ≤20 FTE believe their organizations use the right amount of automation; for every activity, more think they use too little rather than too much, led by analyzing and modeling insights (39% to 4%), preparing and integrating data (36% to 5%), and sourcing participants and data (35% to 2%). Source: GRIT 2026 Insights Practice Report, Greenbook HOW MUCH ORGANIZATION RELIES ON OUTSOURCING (SERVICE-LED: ≤20 FTE) Far too much A bit too much Right amount A bit too little Far too little No opinion Sourcing participants and data 4% 7% 76% 5% 4% 6% Analyzing and modeling insights 2% 7% 73% 9% 5% 3% Preparing and integrating data 2% 5% 81% 3% 3% 4% Designing research and analytics 2% 3% 84% 4% 4% 2% Executing fieldwork and data collection 1% 4% 86% 6% 1% 2% Communicating and activating insights 2% 2% 75% 10% 5% 6% n = 80 Takeaway: Across all activities, more than 70% of service-led suppliers with ≤20 FTE believe they use the right amount of outsourcing, and those who think they use too little are about even with those who think they use too much, except for communicating and activating insights (15% to 4%). Source: GRIT 2026 Insights Practice Report, Greenbook THE BIG PICTURE [STRATEGIC INTERPRETATION] The tasks where agentic AI has achieved its highest adoption are, in this section, still considered under-automated by majorities in several segments — adoption appears to be raising the ceiling rather than satisfying demand. Every segment, without exception, expects automation to increase, and none expects it to abate, though the appetite is unevenly distributed across tasks. Brand-side researchers are the most broadly underserved, viewing automation as insufficient across nearly every task, with gaps of +43% to +49% between “too little” and “too much.” Among suppliers, executing fieldwork and data collection is the task most flagged as under-automated. Communicating and activating insights shows the opposite tension: brand segments want it more automated, while some larger suppliers see it as over-automated even as their appetite to automate it further rivals brand analytics’ — a pull between automation’s strategic value and concern over ceding control of client deliverables. For most of the industry, automation and outsourcing are not substitutes; the largest service-led suppliers are the exception, pursuing more of both at once to restructure overhead while maintaining capacity. One caveat tempers the near-absence of “too much automation” responses: those who felt automation went too far may no longer be in the sample. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Governance & Risks This section looks at whether or not insights organizations have formal guidelines for use of AI, how clear they are, and how confident they are that their organization minimizes the risks of AI misuse. DOES AI GOVERNANCE LEAD TO OVERALL SUCCESS? [ORIENTATION] ORGANIZATION HAS FORMAL RULES ABOUT USE OF AI IN INSIGHTS: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Yes 42% 54% 54% 24% 58% 83% 64% n = 176 152 39 158 79 56 55 Takeaway: Most brand-side analytics professionals (54%), tech-led suppliers (54%), and service-led suppliers with 500+ FTE (64%), 101-500 FTE (83%), and 21-100 FTE (58%) have formal rules about AI use; most brand-side researchers (58%) and service-led suppliers with ≤20 FTE (76%) do not. Source: GRIT 2026 Insights Practice Report, Greenbook CLARITY OF ORGANIZATION’S EXPECTATIONS OF USE OF AI IN INSIGHTS - COMPLETELY/MOSTLY: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Completely/mostly clear 41% 50% 73% 62% 62% 72% 55% n = 176 152 39 158 79 56 55 Takeaway: In each supplier segment, most say their organization’s expectations of AI use in insights are mostly or completely clear, from 55% in service-led suppliers with 500+ FTE to 73% in tech-led, but half or fewer believe that on the brand-side (41% researchers, 50% analytics). Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE ORGANZIATION MINIMIZES RISKS OF AI MISUSE - COMPLETELY/MOSTLY: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Completely/mostly confident 44% 42% 71% 55% 60% 77% 71% n = 176 152 39 158 79 56 55 Takeaway: In each supplier segment, most are confident their organization minimizes the risks of AI misuse, from 55% in service-led suppliers with ≤20 FTE to 77% of those with 101-500 FTE, but less than half believe that on the brand-side (44% researchers, 42% analytics). Source: GRIT 2026 Insights Practice Report, Greenbook AI GOVERNANCE, CLARITY, AND RISK CONFIDENCE | BRAND POV [DATA] ORGANIZATION HAS FORMAL RULES ABOUT USE OF AI IN INSIGHTS: BRAND SEGMENT Yes No, just informal ones No, none at all Don’t know Research (n = 176) 42% 39% 16% 4% Analytics (n = 152) 54% 35% 11% 0% Takeaway: Brand-side analytics professionals are more likely than researchers to say their organization has formal AI governance rules (54% vs. 42%). Source: GRIT 2026 Insights Practice Report, Greenbook CLARITY OF ORGANIZATION’S EXPECTATIONS OF USE OF AI IN INSIGHTS: BRAND SEGMENT Completely clear Mostly clear Somewhat clear Not very clear Not at all clear Don’t use AI tools Research (n = 176) 15% 26% 28% 19% 10% 2% Analytics (n = 152) 7% 43% 31% 15% 4% 1% Takeaway: Brand-side analytics professionals are more likely than researchers to say their organization’s expectations of AI use in insights are completely or mostly clear, 50% to 41%. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE ORGANZIATION MINIMIZES RISKS OF AI MISUSE: BRAND SEGMENT Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Don’t use AI tools No opinion Research (n = 176) 13% 31% 36% 11% 4% 1% 4% Analytics (n = 152) 7% 35% 37% 14% 4% 1% 2% Takeaway: Similar proportions of brand-side analytics professionals (42%) and researchers (44%) are mostly or completely confident their organization minimizes the risks of AI misuse. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH & INSIGHTS/ANALYTICS GOALS: COMPLETELY/MOSTLY CONFIDENT IN AI RISK MANAGEMENT (BRAND: RESEARCH) Exceeded goals Met goals Fell short of goals Completely/mostly confident (n = 86) 57% 30% 13% Less confident (n = 98) 34% 38% 28% Takeaway: Among brand-side researchers, 57% of those who are completely or mostly confident their organization minimizes the risk of AI use exceeded their research insights, and analytics goals; only 34% of those with less confidence exceeded their goals. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH & INSIGHTS/ANALYTICS GOALS: COMPLETELY/MOSTLY CONFIDENT IN AI RISK MANAGEMENT (BRAND: ANALYTICS) Exceeded goals Met goals Fell short of goals Completely/mostly confident (n = 66) 46% 49% 5% Less confident (n = 85) 33% 50% 17% Takeaway: Among brand-side analytics professionals, 46% of those with the most confidence exceeded goals compared to just 33% of the less confident; the least confident in their organization’s ability to minimize the risk of AI misuse were three times as likely to fall short of goals (17% to 5%). Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: HAVE GUIDELINES (BRAND: RESEARCH) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Yes (n = 79) 18% 49% 30% 4% 0% No, just some informal ones (n = 74) 11% 24% 46% 19% 0% No, none at all (n = 26) 6% 22% 30% 14% 28% Takeaway: Of brand-side researchers who have formal guidelines for AI use in insights, 67% are completely/mostly confident their organization minimizes risk of AI misuse compared to just 35% of those with informal guidelines and 28% of those without any guidelines. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: HAVE GUIDELINES (BRAND: ANALYTICS) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Yes (n = 87) 10% 47% 30% 12% 1% No, just some informal ones (n = 52) 3% 23% 51% 16% 7% No, none at all (n = 12) 3% 4% 35% 41% 16% Takeaway: Of brand-side analytics professionals who have formal guidelines for AI use in insights, 57% are completely/mostly confident their organization minimizes risk of AI misuse compared to just 26% of those with informal guidelines and 7% of those without any guidelines. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: CLARITY OF EXPECTATIONS (BRAND: RESEARCH) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Completely/mostly clear (n = 79) 19% 49% 29% 3% 1% Somewhat/not very/not at all clear (n = 104) 9% 23% 43% 19% 7% Takeaway: Of brand-side researchers who say their organization’s expectations of AI use are completely or mostly clear, 68% are completely/mostly confident their organization minimizes risk of AI misuse compared to just 32% of those who think they are less clear. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: CLARITY OF EXPECTATIONS (BRAND: ANALYTICS) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Completely/mostly clear (n = 80) 10% 50% 37% 3% 1% Somewhat/not very/not at all clear (n = 70) 4% 20% 39% 28% 8% Takeaway: Of brand-side analytics professionals who say their organization’s expectations of AI use are completely or mostly clear, 60% are completely/mostly confident their organization minimizes risk of AI misuse compared to just 24% of those who think they are less clear. Source: GRIT 2026 Insights Practice Report, Greenbook AI GOVERNANCE, CLARITY, AND RISK CONFIDENCE | SUPPLIER POV [DATA] ORGANIZATION HAS FORMAL RULES ABOUT USE OF AI IN INSIGHTS: SUPPLIER SEGMENT Yes No, just informal ones No, none at all Don’t know Tech-led (n = 39) 54% 33% 10% 3% Service-led: 500+ FTE (n = 55) 64% 26% 8% 1% Service-led: 101-500 FTE (n = 56) 83% 15% 0% 2% Service-led: 21-100 FTE (n = 79) 58% 37% 3% 3% Service-led: ≤20 FTE (n = 158) 24% 55% 21% 0% Takeaway: Except for service-led suppliers with ≤20 FTE (24%), most suppliers say their organization has formal rules about use of AI in insights, from 54% of tech-led to 83% of service-led with 101-500 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook CLARITY OF ORGANIZATION’S EXPECTATIONS OF USE OF AI IN INSIGHTS: SUPPLIER SEGMENT Completely clear Mostly clear Somewhat clear Not very clear Not at all clear Don’t use AI tools Tech-led (n = 39) 23% 50% 17% 5% 2% 4% Service-led: 500+ FTE (n = 55) 19% 35% 28% 16% 2% 0% Service-led: 101-500 FTE (n = 56) 20% 51% 20% 7% 1% 0% Service-led: 21-100 FTE (n = 79) 17% 44% 32% 3% 1% 2% Service-led: ≤20 FTE (n = 158) 23% 39% 18% 15% 3% 2% Takeaway: In each supplier segment, most say their organization’s expectations of AI use in insights are mostly or completely clear, from 54% in service-led suppliers with 500+ FTE to 73% in tech-led Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE ORGANZIATION MINIMIZES RISKS OF AI MISUSE: SUPPLIER SEGMENT Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Don’t use AI tools No opinion Tech-led (n = 39) 33% 38% 20% 5% 0% 4% 0% Service-led: 500+ FTE (n = 55) 24% 47% 14% 14% 2% 0% 0% Service-led: 101-500 FTE (n = 56) 38% 39% 14% 8% 0% 0% 2% Service-led: 21-100 FTE (n = 79) 20% 40% 20% 8% 1% 7% 5% Service-led: ≤20 FTE (n = 158) 22% 33% 22% 9% 4% 6% 3% Takeaway: In each supplier segment, most are confident their organization minimizes the risks of AI misuse, from 55% in service-led suppliers with ≤20 FTE to 77% of those with 101-500 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH & INSIGHTS/ANALYTICS GOALS: COMPLETELY/MOSTLY CONFIDENT IN AI RISK MANAGEMENT (SERVICE-LED SUPPLIERS) Exceeded goals Met goals Fell short of goals Completely/mostly confident (n = 215) 36% 33% 32% Less confident (n = 103) 19% 43% 37% Takeaway: When service-led suppliers are completely or mostly confident their organizations minimize risk of AI misuse, 36% exceed goals, but 32% fall short; when they lack such confidence, only 19% exceed goals while 37% fall short. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH & INSIGHTS/ANALYTICS GOALS: COMPLETELY/MOSTLY CONFIDENT IN AI RISK MANAGEMENT (SERVICE-LED: >20 FTE) Exceeded goals Met goals Fell short of goals Completely/mostly confident (n = 131) 40% 34% 26% Less confident (n = 51) 18% 47% 35% Takeaway: When service-led suppliers with more than 20 FTE are completely or mostly confident their organizations minimize risk of AI misuse, 40% exceed goals, while 26% fall short; among the less confident, fewer exceed their goals (18%) and more fall short (35%). Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: HAVE GUIDELINES (SERVICE-LED SUPPLIERS) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Yes (n = 160) 35% 42% 15% 8% 0% No, just some informal ones (n = 120) 17% 43% 27% 10% 3% No, none at all (n = 35) 14% 36% 16% 23% 11% Takeaway: Among service-led suppliers who say they have formal guidelines for AI usage in insights, 77% are completely or mostly confident risks are minimized; with only informal guidelines, this drops to 60%, and with no guidelines, it declines to 50%. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: HAVE GUIDELINES (SERVICE-LED: >20 FTE) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Yes (n = 124) 35% 43% 13% 9% 0% No, just some informal ones (n = 49) 9% 51% 31% 7% 2% No, none at all (n = 6) 0% 31% 0% 56% 13% Takeaway: Among service-led suppliers with more than 20 FTE who say they have formal guidelines for AI usage in insights, 78% are completely or mostly confident risks are minimized; with only informal guidelines, this drops to 60%, and with no guidelines, it falls to 31%. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: CLARITY OF EXPECTATIONS (SERVICE-LED SUPPLIERS) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Completely/mostly clear (n = 211) 36% 42% 18% 3% 0% Somewhat/not very/not at all clear (n = 106) 10% 40% 20% 23% 7% Takeaway: Among service-led suppliers who say expectations for AI usage in insights are completely or mostly clear, 78% are completely or mostly confident risks are minimized; when expectations are less clear, this drops to 50%. Source: GRIT 2026 Insights Practice Report, Greenbook CONFIDENCE IN AI RISK MANAGEMENT: CLARITY OF EXPECTATIONS (SERVICE-LED: >20 FTE) Completely confident Mostly confident Somewhat confident Not very confident Not at all confident Completely/mostly clear (n = 119) 38% 44% 15% 3% 0% Somewhat/not very/not at all clear (n = 62) 9% 44% 21% 23% 3% Takeaway: Among service-led suppliers with more than 20 FTE who say expectations for AI usage in insights are completely or mostly clear, 82% are completely or mostly confident risks are minimized; when expectations are less clear, this drops to 53%. Source: GRIT 2026 Insights Practice Report, Greenbook THE BIG PICTURE [STRATEGIC INTERPRETATION] Across the agentic-AI arc, a consistent picture emerges: insights professionals are actively enabling AI expansion through their formal authority over adjacent decisions — supplier selection, technology acquisition, outsourcing — while remaining largely absent from AI governance itself, and it shows in their confidence levels. Confidence that one’s organization minimizes the risk of AI misuse is associated with performance: confident brand-side researchers exceed their goals at 57% versus 34% for the less confident, and among analytics professionals the least confident fall short at roughly three times the rate of the most confident. GRIT is cautious about causality but considers the relationship consistent enough across both brand and supplier segments to take seriously. The brand-side deficit is notable, since brand professionals combine the least formal governance authority with the least confidence in outcomes; fewer than half in either segment are confident their organization minimizes misuse risk, while suppliers are more confident across every segment. Clarity of expectations appears to matter as much as formal rules, and the two reinforce each other. Service-led suppliers with 101–500 FTE lead on governance — 83% with formal rules, 77% confident — the same segment leading on capability and revenue, though these measures dip at 500+ FTE, where organizational complexity may make alignment harder. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Selection Criteria This section reviews how insights professionals across two brand-side segments, researchers and analytics professionals, and five supplier segments, tech-led and four size categories of service-led, prioritize criteria for choosing approaches and methodologies and for selecting suppliers and partners. WHAT’S ‘BETTER’ THAN ‘FASTER’ AND ‘CHEAPER’? [ORIENTATION] TOP THREE PRIORITIES FOR METHOD SELECTION: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Total cost 43.9 36.9 33.2 41.9 31.9 23.6 24.9 Ease of interpreting/communicating results 25.8 21.6 22.4 19.8 25.3 32.5 23.5 Expertise required to produce results 16.3 9.8 15.5 25.4 16.1 18.0 6.9 Speed of results 16.0 19.2 24.9 10.7 9.0 16.6 18.9 Innovative approach 10.5 7.8 3.9 15.9 26.8 20.9 28.5 n = 88 75 19 78 43 27 26 Maxdiff scores. Green shading represents top three in segment. Takeaway: When considering methods, total cost is the top concern in each segment except service-led suppliers with 101-500 FTE; ease of interpreting/communicating results in also in the top three in each segment. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. TOP THREE KEY FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT SEGMENT Brand: research Brand: analytics Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Data quality 88% 76% 91% 87% 90% 87% 84% Service quality 78% 73% 62% 80% 75% 64% 81% General pricing 68% 59% 79% 60% 58% 58% 63% n = 88 75 19 78 43 27 26 Green shading indicates top three within segment. Takeaway: In each segment, the top three criteria for choosing between suppliers are data quality, service quality, and general pricing. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. METHOD AND SUPPLIER SELECTION PRIORITIES | BRAND POV [DATA] KEY PRIORITIES FOR METHOD SELECTION: BRAND SEGMENT Research Analytics Research - analytics Total cost (including services, data, or tools) 43.9 36.9 +7.0 Ease of interpreting and communicating results 25.8 21.6 +4.2 Amount of expertise required to produce results 16.3 9.8 +6.5 Speed of results 16.0 19.2 -3.2 Amount of labor required to produce results 12.8 10.0 +2.8 Innovative approach 10.5 7.8 +2.7 Ease of synthesis with other sources 4.5 12.2 -7.7 Scalability 3.5 15.8 -12.3 n = 88 75 Maxdiff scores. Green shading indicates top three within segment. Takeaway: When selecting methods, both brand-side segments rank total cost and ease of interpreting/communicating results 1-2; speed of results is third for analytics professionals, while amount of expertise required is third for researchers, although in a virtual tie with speed. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) Total cost 1 1 2 1 1 2 1 Ease of interpreting/communicating results -- -- -- -- 2 1 2 Expertise required to produce results -- -- -- -- 6 4 3 Speed of results 2 2 1 2 3 3 4 Labor required to produce results -- -- -- -- 4 6 5 Innovative approach 3 3 3 3 5 5 6 Ease of synthesis with other sources 4 4 4 4 8 7 7 Scalability 4 5 5 5 7 8 8 n = 295 213 203 117 105 129 88 Question changed from rating to maxdiff in 24A. Takeaway: Among brand-side researchers, total cost and ease of interpreting/communicating results have been top two concerns when selecting methods in each year they were presented, while expertise required has climbed into third place. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A Total cost 1 2 1 1 Ease of interpreting/communicating results -- 1 2 2 Speed of results 2 3 6 3 Scalability 5 6 4 4 Ease of synthesis with other sources 4 7 8 5 Labor required to produce results -- 8 5 6 Expertise required to produce results -- 4 3 7 Innovative approach 3 5 7 8 n = 133 97 121 75 Question changed from rating to maxdiff in 24A. Takeaway: Brand-side analytics professionals look for methods that perform well on cost, ease of interpreting/communicating results, and speed. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. KEY DECISION FACTORS - MAJORITY IN EITHER SEGMENT: BRAND SEGMENT Research Analytics Data quality 88% 76% Service quality 78% 73% General pricing 68% 59% Reputation 32% 55% Use of technology in research and analysis 28% 51% n = 88 75 Takeaway: In both brand-side segments, most identify data quality, service quality, and general pricing as key factors when choosing between suppliers, and majorities of analytics professionals also name reputation (55%) and use of technology in research and analytics (51%) as key. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS - MINORITY IN BOTH SEGMENTS: BRAND SEGMENT Research Analytics Relationship with me or my organization 40% 28% Thought leadership 39% 45% Innovative approach or tools 29% 41% Use of technology in communication or sharing 22% 34% Negotiated rate cards 16% 28% Local to me 10% 10% Global offices 10% 15% Support for social causes or issues 6% 11% Size of organization 6% 9% Diversity of staff 6% 10% n = 88 75 Takeaway: Among factors that are not considered key when choosing between suppliers by a majority in either segment, relationship (40%) and thought leadership (39%) lead among brand-side researchers and thought leadership (45%) and innovative approach (41%) lead among analytics. Source: GRIT 2026 Insights Practice Report, Greenbook TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (BRAND: RESEARCH) Key factor Significant Data quality 88% 12% Service quality 78% 20% General pricing 68% 30% Reputation 32% 62% Innovative approach or tools 29% 61% Relationship with me/organization 40% 45% Thought leadership 39% 44% Use of tech in research/analysis 28% 50% Use of tech in communication/sharing 22% 42% Negotiated rate cards 16% 46% n = 88 Takeaway: When considering which factors are considered key or significant when choosing between suppliers, reputation (94%) and innovation (90%) emerge as top-of-mind among brand-side researchers. Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (BRAND: RESEARCH) Key factor Significant Size of organization 6% 32% Global offices 10% 23% Diversity of staff 6% 26% Local to me 10% 22% Support for social causes or issues 6% 17% n = 88 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, size of organization (38%) stands out among brand-side researchers. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (BRAND: RESEARCH) 20A (Aggregate) 21A (Aggregate) 22A (Aggregate) 23A (Research) 24A (Research) 25A (Research) 26A (Research) 26A – 25A Data quality 85% 80% 80% 91% 80% 86% 88% +2% Service quality 58% 56% 53% 83% 73% 87% 78% -9% General pricing 46% 41% 43% 44% 51% 59% 68% +9% Relationship with me or my organization 50% 37% 33% 35% 40% 45% 40% -5% Thought leadership 44% 38% 35% 45% 48% 47% 39% -8% Reputation 42% 37% 32% 43% 39% 46% 32% -14% Innovative approach or tools 40% 39% 33% 34% 31% 40% 29% -11% Use of technology in research and analysis** 25% 30% 25% 26% 26% 31% 28% -3% Use of technology in communication or sharing * 17% 15% 18% 19% 18% 22% +4% Negotiated rate cards 15% 14% 12% 11% 22% 17% 16% -1% Local to me 13% 8% 3% 7% 10% 12% 10% -2% Global offices 11% 8% 4% 10% 8% 9% 10% +1% Support for social causes or issues * 8% 5% 2% 6% 5% 6% +1% Size of organization 4% 6% 4% 4% 9% 5% 6% +1% Diversity of staff * 10% 6% 5% 7% 8% 6% -2% Average number of factors: 4.3 4.3 3.8 4.6 4.7 5.2 4.8 +0.4 n = 298 215 203 117 105 129 88 * Not asked in 20A **Asked as “Use of technology” in 20A Green shading indicates top five within wave. Takeaway: Among brand-side researchers, data quality (88%), service quality (78%), general pricing (68%), and thought leadership (39%) are perennially top key factors, and relationship (40%) moved back into the top five in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (BRAND: ANALYTICS) Key factor Significant Reputation 55% 44% Service quality 73% 24% Data quality 76% 20% Use of tech in research/analysis 51% 44% General pricing 59% 35% Use of tech in communication/sharing 34% 55% Thought leadership 45% 44% Innovative approach or tools 41% 46% Relationship with me/organization 28% 57% Negotiated rate cards 28% 55% n = 77 Takeaway: When considering factors which are considered key or significant when choosing between suppliers, several emerge as top-of-mind among brand-side analytics professionals, led by reputation (99%) and use of technology in research and analysis (95%). Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (BRAND: ANALYTICS) Key factor Significant Size of organization 9% 57% Global offices 15% 29% Local to me 10% 33% Support for social causes or issues 11% 29% Diversity of staff 10% 31% n = 77 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, size of organization (66%) stands out among brand-side analytics. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (BRAND: ANALYTICS) 23A 24A 25A 26A 26A - 25A Data quality 79% 69% 86% 76% -10% Service quality 73% 63% 63% 73% +10% General pricing 47% 61% 52% 59% +7% Reputation 52% 62% 54% 55% +1% Use of tech in research/analysis 52% 44% 48% 51% +3% Thought leadership 43% 47% 33% 45% +12% Innovative approach or tools 45% 38% 37% 41% +4% Use of tech in communication/sharing 39% 32% 34% 34% -- Negotiated rate cards 17% 25% 19% 28% +9% Relationship with me/organization 36% 29% 25% 28% +3% Global offices 10% 15% 12% 15% +3% Support for social causes or issues 17% 10% 10% 11% +1% Diversity of staff 19% 14% 7% 10% +3% Local to me 15% 11% 5% 10% +5% Size of organization 15% 18% 5% 9% +4% Average number of factors: 5.6 5.4 4.9 5.4 +0.5 n = 133 97 121 77 Green shading indicates top five within wave. Takeaway: Among brand-side analytics professionals, data quality (76%), service quality (73%), general pricing (59%), and reputation (55%) are perennial top-five key factors when choosing between suppliers. Source: GRIT 2026 Insights Practice Report, Greenbook, with NewtonX. METHOD AND SUPPLIER SELECTION PRIORITIES | SUPPLIER POV [DATA] KEY PRIORITIES FOR METHOD SELECTION: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Innovative approach 3.9 15.9 26.8 20.9 28.5 Total cost (including services, data, or tools) 33.2 41.9 31.9 23.6 24.9 Ease of interpreting and communicating results 22.4 19.8 25.3 32.5 23.5 Speed of results 24.9 10.7 9.0 16.6 18.9 Scalability 18.8 3.7 12.8 11.8 18.3 Amount of expertise required to produce results 15.5 25.4 16.1 18.0 6.9 Ease of synthesis with other sources 1.9 5.9 4.8 2.6 6.7 Amount of labor required to produce results 12.7 10.1 6.6 7.4 5.6 n = 19 78 43 27 26 Maxdiff scores. Green shading represents top three in segment. Takeaway: Across supplier segments, total cost and ease of interpreting/communicating results are among the three most important factors when selecting methodologies; innovative approach is a top-three concern for service-led suppliers with 20+ FTE, amount of expertise required for those with ≤20 FTE, and speed of results for tech-led. Source: GRIT 2026 Insights Practice Report, Greenbook. KEY DECISION FACTORS - MAJORITY IN ANY SEGMENT: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Data quality 91% 87% 90% 87% 84% Service quality 62% 80% 75% 64% 81% General pricing 79% 60% 58% 58% 63% Innovative approach or tools 17% 18% 45% 36% 51% Reputation 49% 48% 46% 57% 47% Use of technology in research and analysis 52% 19% 29% 36% 36% Relationship with me or my organization 47% 57% 51% 51% 35% Average number of factors: 5.4 4.4 4.9 4.9 5.4 n = 19 78 43 27 26 Green shading indicates top five within segment. Takeaway: Data quality, service quality, and general pricing are considered key factors when choosing suppliers by majorities in each segment, and reputation is also in the top five for each. Rounding out the top five, tech-led suppliers mention use of technology in research/analysis, service-led with 500+ FTE mention innovative approach, and the others mention relationship. Source: GRIT 2026 Insights Practice Report, Greenbook. KEY DECISION FACTORS – MINORITY IN EACH SEGMENT: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Thought leadership 23% 18% 27% 19% 30% Use of technology in communication or sharing 46% 13% 20% 21% 29% Global offices 3% 5% 12% 7% 22% Negotiated rate cards 43% 16% 15% 16% 17% Support for social causes or issues 4% 4% 2% 7% 17% Diversity of staff 3% 3% 3% 16% 13% Size of organization -- 2% 4% 3% 13% Local to me 21% 9% 12% 7% 6% Average number of factors: 5.4 4.4 4.9 4.9 5.4 n = 19 78 43 27 26 Green shading indicates top five within segment. Takeaway: Among key supplier choice priorities that are not in the top five in any segment, use of technology in communication and sharing (46%) and negotiated rate cards (43%) among tech-led suppliers stand out. Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD AND SUPPLIER SELECTION PRIORITIES | TECH-LED POV [DATA] KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A Total cost 4 4 4 4 1 5 1 Speed of results 2 1 1 1 3 4 2 Ease of interpreting/communicating results -- -- -- -- 5 2 3 Scalability 1 1 2 2 4 3 4 Expertise required to produce results -- -- -- -- 8 6 5 Labor required to produce results -- -- -- -- 6 7 6 Innovative approach 3 3 2 3 2 1 7 Ease of synthesis with other sources 5 5 5 5 7 8 8 n = 92 52 117 47 29 27 19 Takeaway: Among method selection priorities for tech-led suppliers, total cost has returned to the top, speed is back up to second, and ease of interpreting/communicating results is third; innovative approach has fallen from first to seventh. Source: GRIT 2026 Insights Practice Report, Greenbook. TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (TECH-LED) Key factor Significant Service quality 62% 38% General pricing 79% 21% Data quality 91% 9% Reputation 49% 43% Relationship with me/organization 47% 44% Use of tech in research/analysis 52% 35% Use of tech in communication/sharing 46% 35% Thought leadership 23% 55% Innovative approach or tools 17% 60% Negotiated rate cards 43% 31% n = 19 Takeaway: When considering factors which are considered key or significant when choosing between suppliers, several emerge as top-of-mind among tech-led, led by reputation (92%) and relationship (91%). Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (TECH-LED) Key factor Significant Size of organization 0% 39% Local to me 21% 16% Diversity of staff 3% 29% Global offices 3% 25% Support for social causes or issues 4% 24% n = 19 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, size of organization (39%) and local (37%) stand out among tech-led suppliers. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (TECH-LED) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Data quality 78% 81% 74% 89% 77% 94% 91% -3% General pricing 46% 38% 35% 42% 55% 44% 79% +35% Service quality 60% 37% 48% 78% 59% 82% 62% -20% Use of tech in research/analysis** 61% 60% 50% 65% 22% 47% 52% +5% Reputation 45% 37% 32% 46% 40% 38% 49% +11% Relationship with me/organization 49% 37% 32% 38% 48% 59% 47% -12% Use of tech in communication/sharing* -- 27% 23% 38% 27% 46% 46% -- Negotiated rate cards 16% 10% 13% 14% 22% 19% 43% +24% Thought leadership 35% 19% 20% 28% 14% 39% 23% -16% Local to me 6% 6% 4% 6% 5% 18% 21% +3% Innovative approach or tools 47% 44% 48% 43% 28% 66% 17% -49% Support for social causes or issues* -- 10% 7% 11% 7% 14% 4% -10% Diversity of staff* -- 12% 7% 4% 5% 9% 3% -6% Global offices 8% 10% 8% 14% -- 17% 3% -14% Size of organization 3% 6% 7% 10% 13% 14% -- -14% Average number of factors: 4.6 4.3 4.1 5.3 4.2 6.1 5.4 -0.7 n = 97 52 117 47 29 27 19 Green shading indicates top five within wave. * Not asked in 20A **Asked as “Use of technology” in 20A Takeaway: Among tech-led suppliers, general pricing increased as a key factor when choosing between suppliers, from 44% in 25A to 79% in 26A, as did negotiated rate cards (19% to 43%); innovative approach fell (66% to 17%). Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD AND SUPPLIER SELECTION PRIORITIES | SERVICE-LED: 500+ FTE POV [DATA] KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A Innovative approach 3 2 2 2 4 1 1 Total cost 1 4 4 3 1 3 2 Ease of interpreting/communicating results -- -- -- -- 2 2 3 Speed of results 1 1 1 1 3 5 4 Scalability 4 3 3 4 5 4 5 Expertise required to produce results -- -- -- -- 7 6 6 Ease of synthesis with other sources 5 5 5 5 8 7 7 Labor required to produce results -- -- -- -- 6 8 8 n = 104 94 124 63 42 44 26 Takeaway: Among method selection priorities for service-led suppliers with 500+ FTE, innovative approach is the top concern, followed by total cost and ease of interpreting/communicating results. Source: GRIT 2026 Insights Practice Report, Greenbook. TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: 500+ FTE) Key factor Significant Service quality 81% 19% Data quality 84% 16% General pricing 63% 34% Innovative approach or tools 51% 39% Use of tech in research/analysis 36% 50% Relationship with me/organization 35% 50% Reputation 47% 34% Thought leadership 30% 49% Negotiated rate cards 17% 61% Use of tech in communication/sharing 29% 43% n = 26 Takeaway: When considering factors which are considered key or significant when choosing between suppliers, several emerge as top-of-mind among service-led suppliers with 500+ FTE, led by innovative approach (90%), use of technology in research/analysis (86%), and relationship (85%). Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: 500+ FTE) Key factor Significant Global offices 22% 37% Size of organization 13% 41% Local to me 6% 34% Diversity of staff 13% 26% Support for social causes or issues 17% 3% n = 26 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, global offices (59%) and size of organization (54%) stand out among service-led suppliers with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (SERVICE-LED: 500+ FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Data quality 88% 90% 80% 87% 76% 83% 84% +1% Service quality 67% 59% 61% 85% 31% 79% 81% +2% General pricing 53% 49% 36% 53% 64% 47% 63% +16% Innovative approach or tools 42% 46% 52% 28% 23% 29% 51% +22% Reputation 55% 47% 52% 47% 57% 53% 47% -6% Use of tech in research/analysis** 48% 34% 48% 35% 30% 31% 36% +5% Relationship with me/organization 46% 47% 40% 43% 38% 52% 35% -17% Thought leadership 39% 31% 33% 17% 29% 31% 30% -1% Use of tech in communication/sharing* -- 20% 31% 18% 27% 26% 29% +3% Global offices 16% 17% 19% 18% 9% 6% 22% +16% Negotiated rate cards 15% 23% 23% 28% 30% 21% 17% -4% Support for social causes or issues* -- 14% 15% 1% 15% 5% 17% +12% Diversity of staff* -- 17% 16% 3% 11% 11% 13% +2% Size of organization 8% 11% 15% 5% 13% 9% 13% +4% Local to me 8% 7% 12% 4% 10% 18% 6% -12% Average number of factors: 4.9 5.1 5.3 4.7 4.6 5.0 5.4 +0.4 n = 106 94 124 63 42 44 26 Green shading indicates top five within wave. * Not asked in 20A **Asked as “Use of technology” in 20A Takeaway: Among service-led suppliers with 500+ FTE, innovative approach increased as a key factor when choosing between suppliers, from 29% in 25A to 51% in 26A; general pricing (47% to 63%) and global offices (6% to 22%) also rose. Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD AND SUPPLIER SELECTION PRIORITIES | SERVICE-LED: 101-500 FTE POV [DATA] KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A Ease of interpreting/communicating results -- -- -- -- 1 2 1 Total cost 1 3 3 3 6 1 2 Innovative approach 3 2 2 2 2 4 3 Expertise required to produce results -- -- -- -- 5 6 4 Speed of results 1 1 1 1 3 3 5 Scalability 4 4 3 4 4 7 6 Labor required to produce results -- -- -- -- 7 5 7 Ease of synthesis with other sources 5 5 5 5 8 8 8 n = 106 86 132 55 48 44 27 Takeaway: Among method selection priorities for service-led suppliers with 101-500 FTE, ease of interpreting/communicating results is the top concern, followed by total cost and innovative approach. Source: GRIT 2026 Insights Practice Report, Greenbook. TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: 101-500 FTE) Key factor Significant Data quality 87% 13% Service quality 64% 36% General pricing 58% 42% Relationship with me/organization 51% 44% Innovative approach or tools 36% 52% Reputation 57% 29% Negotiated rate cards 16% 62% Use of tech in communication/sharing 21% 54% Use of tech in research/analysis 36% 38% Thought leadership 19% 53% n = 27 Takeaway: When considering factors which are considered key or significant when choosing between suppliers, several emerge as top-of-mind among service-led suppliers with 101-500 FTE, led by relationship (95%), use of innovative approach (88%), and reputation (86%). Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: 101-500 FTE) Key factor Significant Diversity of staff 16% 17% Support for social causes or issues 7% 16% Size of organization 3% 16% Local to me 7% 11% Global offices 7% 9% n = 27 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, diversity of staff (33%) stands out among service-led suppliers with 101-500 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (SERVICE-LED: 101-500 FTE) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Data quality 87% 86% 89% 96% 88% 90% 87% -3% Service quality 62% 57% 61% 79% 83% 84% 64% -20% General pricing 49% 49% 47% 51% 61% 59% 58% -1% Reputation 52% 41% 52% 54% 59% 58% 57% -1% Relationship with me/organization 57% 40% 45% 49% 44% 50% 51% +1% Use of tech in research/analysis** 30% 31% 37% 36% 46% 39% 36% -3% Innovative approach or tools 31% 38% 41% 46% 50% 36% 36% -- Use of tech in communication/sharing* -- 19% 26% 14% 34% 23% 21% -2% Thought leadership 34% 28% 35% 25% 35% 21% 19% -2% Negotiated rate cards 15% 15% 13% 23% 21% 30% 16% -14% Diversity of staff* -- 9% 15% 6% 13% 2% 16% +14% Local to me 6% 13% 13% 4% 14% 10% 7% -3% Support for social causes or issues* -- 3% 8% 2% 13% 5% 7% +2% Global offices 7% 3% 8% 4% 19% 9% 7% -2% Size of organization 6% 2% 6% 6% 19% 5% 3% -2% Average number of factors: 4.4 4.3 5.0 5.0 6.0 5.2 4.9 -0.3 n = 108 86 132 55 48 44 27 Green shading indicates top five within wave. * Not asked in 20A **Asked as “Use of technology” in 20A Takeaway: Among service-led suppliers with 101-500 FTE, service quality declined as a key factor when choosing between suppliers, from 84% in 25A to 64% in 26A, although it is still second. Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD AND SUPPLIER SELECTION PRIORITIES | SERVICE-LED: 21-100 FTE POV [DATA] KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A Total cost 1 2 3 1 2 3 1 Innovative approach 3 1 1 2 4 1 2 Ease of interpreting/communicating results -- -- -- -- 1 2 3 Expertise required to produce results -- -- -- -- 3 5 4 Scalability 4 4 4 4 6 8 5 Speed of results 2 3 2 3 5 4 6 Labor required to produce results -- -- -- -- 7 7 7 Ease of synthesis with other sources 5 5 5 5 8 6 8 n = 167 143 140 131 63 54 43 Takeaway: Among method selection priorities for service-led suppliers with 21-100 FTE, total cost is most important, followed by innovative approach and ease of interpreting/communicating results. Source: GRIT 2026 Insights Practice Report, Greenbook. TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: 21-100 FTE) Key factor Significant Data quality 90% 9% General pricing 58% 39% Relationship with me/organization 51% 45% Service quality 75% 21% Reputation 46% 49% Innovative approach or tools 45% 47% Use of tech in research/analysis 29% 55% Negotiated rate cards 15% 61% Use of tech in communication/sharing 20% 53% Thought leadership 27% 43% n = 43 Takeaway: When considering factors which are considered key or significant when choosing between suppliers, several emerge as top-of-mind among service-led suppliers with 21-100 FTE, led by relationship (96%), reputation (95%), and innovative approach (92%). Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: 21-100 FTE) Key factor Significant Global offices 12% 35% Local to me 12% 26% Support for social causes or issues 2% 33% Diversity of staff 3% 31% Size of organization 4% 24% n = 43 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, global offices (47%) and local (38%) stand out among service-led suppliers with 21-100 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (SERVICE-LED: 21-100 FTE) 20A 21A 22A 23A 24A 25A 26A 26A - 25A Data quality 87% 86% 83% 88% 95% 93% 90% -3% Service quality 63% 55% 62% 81% 86% 77% 75% -2% General pricing 47% 45% 44% 55% 56% 61% 58% -3% Relationship with me/organization 56% 35% 44% 47% 47% 52% 51% -1% Reputation 50% 41% 44% 49% 53% 52% 46% -6% Innovative approach or tools 40% 43% 44% 39% 44% 31% 45% +14% Use of tech in research/analysis** 33% 36% 36% 37% 43% 34% 29% -5% Thought leadership 33% 26% 36% 23% 40% 16% 27% +11% Use of tech in communication/sharing* -- 24% 26% 28% 29% 27% 20% -7% Negotiated rate cards 12% 14% 12% 19% 16% 28% 15% -13% Local to me 9% 6% 6% 9% 14% 12% 12% -- Global offices 7% 8% 8% 9% 14% 3% 12% +9% Size of organization 4% 7% 4% 9% 12% 5% 4% -1% Diversity of staff* -- 8% 6% 9% 13% 8% 3% -5% Support for social causes or issues* -- 8% 9% 10% 12% 14% 2% -12% Average number of factors: 4.4 4.4 4.6 5.1 5.7 5.1 4.9 -0.3 n = 169 143 140 131 63 54 43 Green shading indicates top five within wave. * Not asked in 20A **Asked as “Use of technology” in 20A Takeaway: Among service-led suppliers with 21-100 FTE, data quality (90%), service quality (75%), general pricing (58%), and reputation (46%) are perennial top-five key factors when choosing between suppliers. Source: GRIT 2026 Insights Practice Report, Greenbook. METHOD AND SUPPLIER SELECTION PRIORITIES | SERVICE-LED: ≤20 FTE POV [DATA] KEY PRIORITY RANK FOR METHOD SELECTION: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A Total cost 1 1 3 1 1 2 1 Expertise required to produce results -- -- -- -- 4 3 2 Ease of interpreting/communicating results -- -- -- -- 2 1 3 Innovative approach 3 2 1 3 3 4 4 Speed of results 2 3 1 2 6 5 5 Labor required to produce results -- -- -- -- 5 6 6 Ease of synthesis with other sources 4 4 4 5 7 8 7 Scalability 5 5 5 4 8 7 8 n = 307 213 222 164 77 96 78 Takeaway: Among method selection priorities for service-led suppliers with ≤20 FTE, total cost is most important, expertise required to produce results has emerged as second, and ease of interpreting/communicating results is third. Source: GRIT 2026 Insights Practice Report, Greenbook. TOP 10 FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: ≤20 FTE) Key factor Significant Service quality 80% 18% Data quality 87% 9% Reputation 48% 48% General pricing 60% 36% Relationship with me/organization 57% 29% Innovative approach or tools 18% 64% Use of tech in research/analysis 19% 53% Thought leadership 18% 45% Use of tech in communication/sharing 13% 45% Negotiated rate cards 16% 29% n = 78 Takeaway: When considering factors which are considered key or significant when choosing between suppliers, some emerge as top-of-mind among service-led suppliers with ≤20 FTE, led by reputation (96%). Source: GRIT 2026 Insights Practice Report, Greenbook OTHER FACTORS IN PARTNER/SUPPLIER SELECTION (SERVICE-LED: ≤20 FTE) Key factor Significant Local to me 9% 20% Size of organization 2% 24% Global offices 5% 21% Support for social causes or issues 4% 19% Diversity of staff 3% 18% n = 78 Takeaway: Of the lower-ranked factors according to key or significant consideration when choosing between suppliers, local (29%) stands out the most among service-led suppliers with ≤20 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook KEY DECISION FACTORS IN PARTNER/SUPPLIER SELECTION: GRIT WAVE (SERVICE-LED: ≤20 FTE) 20A 21A 22A 23A 24A 25A 26A 26A – 25A Data quality 83% 85% 83% 91% 84% 86% 87% +1% Service quality 66% 64% 62% 80% 72% 87% 80% -7% General pricing 48% 46% 45% 51% 54% 57% 60% +3% Relationship with me/organization 59% 51% 52% 56% 53% 66% 57% -9% Reputation 47% 39% 42% 50% 46% 51% 48% -3% Use of tech in research/analysis** 25% 31% 33% 29% 37% 28% 19% -9% Innovative approach or tools 34% 40% 34% 34% 45% 31% 18% -13% Thought leadership 27% 30% 24% 26% 26% 25% 18% -7% Negotiated rate cards 11% 9% 14% 7% 18% 17% 16% -1% Use of tech in communication/sharing* -- 20% 19% 16% 34% 15% 13% -2% Local to me 8% 14% 9% 4% 8% 8% 9% +1% Global offices 4% 4% 7% 3% 6% 5% 5% -- Support for social causes or issues* -- 8% 8% 2% 9% 6% 4% -2% Diversity of staff* -- 10% 7% 4% 8% 2% 3% +1% Size of organization 3% 4% 5% 1% 10% 1% 2% +1% Average number of factors: 4.2 4.6 4.5 4.5 5.1 4.9 4.4 -0.5 n = 310 213 222 164 77 96 78 Green shading indicates top five within wave. * Not asked in 20A **Asked as “Use of technology” in 20A Takeaway: Among service-led suppliers with ≤20 FTE, data quality (87%), service quality (80%), general pricing (60%), and relationship (57%) are perennial top-five key factors when choosing between suppliers. Source: GRIT 2026 Insights Practice Report, Greenbook. THE BIG PICTURE [STRATEGIC INTERPRETATION] Method selection and supplier selection answer different questions. Choosing a method evaluates something you will do, so the constraints are internal and the risks operational — and total cost is a near-universal top concern, now joined by ease of interpreting and communicating results as an emerging must-have, even as speed fades as a standalone factor. The shift suggests a progression from feeling pressure to be faster toward understanding how to actually achieve useful results. Tech-led suppliers are the exception: total cost dominates, speed returns to second, and innovative approach collapsed from first to seventh, consistent with optimizing for competitive delivery rather than capability breadth. Choosing a supplier evaluates a relationship, so the risks are relational and reputational; data quality, service quality, and pricing are stable table stakes across all segments and waves. Innovation reads more as a selling point than a buying criterion — it ranks low for method selection but surfaces more in supplier choice, especially among service-led suppliers, where global reach rose in importance while relationship fell sharply, fitting the broader transformation seen elsewhere. One notable movement is thought leadership: consistently top-five for brand-side researchers and up +12% to 45% among brand analytics, though no higher than eighth in any supplier segment. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Business Outlook This section discusses trends in research project budgets, supplier revenue, tech spending, staff sizes, and outsourcing, all from the perspectives of brand-side research and analytics professionals as well as service-led suppliers across size bands and tech-led suppliers. TECHNOLOGY IS THE VEHICLE — WHAT’S THE DESTINATION? [ORIENTATION] TECH SPENDING TREND: GRIT SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Research (n = 163) 14% 41% 38% 5% 2% Analytics (n = 151) 27% 51% 18% 3% 1% Tech-led (n = 37) 28% 44% 26% 3% 0% Service-led: 500+ FTE (n = 50) 33% 49% 18% 0% 0% Service-led: 101-500 FTE (n = 51) 24% 51% 24% 0% 0% Service-led: 21-100 FTE (n = 76) 16% 50% 25% 7% 1% Service-led: ≤20 FTE (n = 152) 9% 32% 50% 7% 2% Takeaway: In every GRIT segment except service-led suppliers with ≤20 FTE, most report increases in technology spending in the past year, from 55% of brand-side researchers to 82% of service-led suppliers with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Research (n = 172) 3% 23% 44% 24% 6% Analytics (n = 150) 5% 35% 51% 9% 0% Tech-led (n = 39) 18% 27% 33% 20% 2% Service-led: 500+ FTE (n = 52) 7% 21% 42% 26% 4% Service-led: 101-500 FTE (n = 55) 13% 29% 37% 11% 9% Service-led: 21-100 FTE (n = 77) 14% 34% 26% 17% 9% Service-led: ≤20 FTE (n = 155) 6% 9% 69% 13% 4% Takeaway: Increases in staff size were not reported by majorities in any segment, but in four segments, at least 40% reported staff size increases: brand-side analytics (40%), tech-led suppliers (45%), service-led suppliers with 101 to 500 FTE (42%), and those with 21 to 100 FTE (48%). Source: GRIT 2026 Insights Practice Report, Greenbook RESEARCH SPENDING AND REVENUE TRENDS [DATA] REVENUE INCREASES: GRIT WAVE BY SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE 20A 62% 46% 60% 64% 65% 21A 63% 28% 36% 23% 26% 22A 79% 55% 74% 79% 87% 23A 72% 58% 74% 81% 88% 24A 58% 46% 60% 56% 55% 25A 73% 44% 60% 63% 53% 26A 58% 37% 54% 59% 51% Takeaway: Revenue increases among supplier segments peaked during recovery from the pandemic 22A–23A, however, in 26A all segments show fewer increases since 25A. Source: GRIT 2026 Insights Practice Report, Greenbook RESEARCH PROJECT SPEND INCREASES: GRIT WAVE BY BRAND SEGMENT Research Analytics 20A 34% 21A 33% 22A 37% 23A 40% 51% 24A 40% 38% 25A 34% 42% 26A 35% 53% Takeaway: Brand-side researchers’ project spending increases peaked from 22A to 24A, reaching 40%, but have fallen back to 35% this year; analytics professionals report a stronger but more volatile pattern, rebounding from 38% in 24A to 53% in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook TRENDS OVERVIEW | BRAND POV [DATA] KEY TRENDS INDICES: BRAND SEGMENT Research Analytics Research project spending 1.4 55.8 Insights staff size -5.7 36.8 Technology spending 60.1 99.3 Takeaway: Research spending, staff size, and technology spending are stronger among brand-side analytics professionals than among researchers; for each segment, technology spending is the strongest trend (99.3 index for analytics; 60.1 for researchers). Source: GRIT 2026 Insights Practice Report, Greenbook KEY TRENDS INDICES: GRIT WAVE (BRAND: RESEARCH) Research project spending Insights staff size Technology spending 20A (Aggregate) 8.0 6.7 45.9 21A (Aggregate) -0.8 2.6 27.6 22A (Aggregate) 23.0 21.2 44.1 23A (Research) 30.3 22.0 53.2 24A (Research) 30.4 19.0 46.9 25A (Research) 8.7 0.4 35.6 26A (Research) 1.4 -5.7 60.1 Takeaway: Among brand-side researchers, the technology spending index just peaked in 26A (60.1), while research project spending continued to drop to near zero (1.4); the staff size index turned negative (–5.7) for the first time. Source: GRIT 2026 Insights Practice Report, Greenbook KEY TRENDS INDICES: GRIT WAVE (BRAND: ANALYTICS) Research project spending Insights staff size Technology spending 23A 43.5 41.2 72.8 24A 27.9 41.6 61.8 25A 39.2 24.5 78.7 26A 55.8 36.8 99.3 Takeaway: For brand-side analytics professionals, all three indices improved in 26A: research spending (from 39.2 to 55.8), staff size (from 24.5 to 36.8), and technology spending (from 78.7 to 99.3). Source: GRIT 2026 Insights Practice Report, Greenbook PROJECT BUDGET TRENDS | BRAND POV [DATA] ANNUAL RESEARCH PROJECT SPENDING TREND: BRAND SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Research (n = 169) 6% 28% 35% 21% 9% Analytics (n = 150) 13% 41% 37% 9% 0% Takeaway: Brand-side analytics professionals experienced substantially more budget increases than researchers (54% to 34% for research). Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT SPENDING TREND: GRIT WAVE (BRAND: RESEARCH) Increase About the same Decrease 14AB (Aggregate; n = 239) 43% 44% 13% 16A (Aggregate; n = 196) 45% 42% 13% 17A (Aggregate; n = 322) 45% 36% 19% 18A (Aggregate; n = 316) 35% 38% 27% 19A (Aggregate; n = 303) 35% 38% 27% 20A (Aggregate, n = 288) 34% 39% 27% 21A (Aggregate, n = 262) 33% 37% 30% 22A (Aggregate, n = 236) 44% 49% 8% 23A (Research, n = 203) 40% 43% 18% 24A (Research, n = 182) 40% 44% 16% 25A (Research, n = 197) 34% 44% 22% 26A (Research, n = 169) 35% 35% 30% Takeaway: Brand-side researchers reporting decreases in project spending reached 30% in 26A, matching the high from 21A and reversing a period of relative stability. Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT SPENDING TREND: GRIT WAVE (BRAND: ANALYTICS) Increase About the same Decrease 23A (n = 170) 51% 36% 14% 24A (n = 187) 38% 46% 16% 25A (n = 171) 42% 50% 8% 26A (n = 150) 53% 37% 10% Takeaway: Brand-side analytics professionals’ spending growth is at its strongest since tracking began, with 53% reporting increases in 26A, up from 42% in 25A. Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT BUDGET SIZE: BRAND SEGMENT Under $1MM $1MM to $3MM $3MM to $10MM $10MM to $30MM More than $30MM Research (n = 152) 41% 23% 19% 9% 8% Analytics (n = 136) 15% 12% 23% 25% 26% Takeaway: Brand-side analytics professionals operate with substantially larger budgets than researchers: 51% have budgets of $10MM or more vs. only 17% of researchers. Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT BUDGET SIZE: GRIT WAVE (BRAND: RESEARCH) Under $1MM $1MM to $3MM $3MM to $10MM $10MM to $15MM More than $15MM 18A (Aggregate, n = 298) 37% 22% 18% 6% 16% 19A (Aggregate, n = 286) 32% 26% 23% 5% 14% 20A (Aggregate, n = 255) 36% 28% 19% 4% 13% 21A (Aggregate, n = 221) 43% 22% 17% 5% 12% 22A (Aggregate, n = 195) 44% 23% 17% 5% 11% 23A (Research, n = 179) 54% 24% 7% 3% 12% 24A (Research, n = 158) 39% 26% 13% 2% 19% 25A (Research, n = 178) 40% 20% 21% 6% 13% 26A (Research, n = 152) 41% 23% 19% 5% 12% Takeaway: The budget distribution for brand-side researchers has been mostly stable for two years since 24A with 39% to 41% under $1MM, although budgets of 15MM+ have fallen from 19% to 12%. Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT BUDGET SIZE: GRIT WAVE (BRAND: ANALYTICS) Under $1MM $1MM to $3MM $3MM to $10MM $10MM to $15MM More than $15MM 23A (n = 149) 34% 19% 15% 6% 26% 24A (n = 168) 22% 21% 27% 3% 26% 25A (n = 159) 25% 17% 24% 6% 27% 26A (n = 136) 15% 12% 23% 10% 40% Takeaway: Brand-side analytics professionals’ budget sizes shifted upward in 26A: those with budgets over $15MM grew from 27% in 25A to 40%, the highest level in the tracked period. Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT SPENDING TREND: BUDGET SIZE (BRAND: RESEARCH) Increase About the same Decrease Under $3MM (n = 91) 31% 37% 32% $3MM to 15MM (n = 35) 34% 38% 27% More than $15MM (n = 25) 50% 26% 24% Takeaway: Among brand-side researchers, those with budgets of more than $15MM reported the most budget increases (50%). Source: GRIT 2026 Insights Practice Report, Greenbook ANNUAL RESEARCH PROJECT SPENDING TREND: BUDGET SIZE (BRAND: ANALYTICS) Increase About the same Decrease Under $3MM (n = 37) 48% 45% 7% $3MM to 15MM (n = 50) 57% 33% 9% More than $15MM (n = 49) 52% 35% 13% Takeaway: Among brand-side analytics professionals, those with budgets of $3MM to $15MM reported the most budget increases (57%). Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING AND STAFFING TRENDS | BRAND POV [DATA] TECH SPENDING TREND: BRAND SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Research (n = 163) 14% 41% 38% 5% 2% Analytics (n = 151) 27% 51% 18% 3% 1% Takeaway: Majorities in each brand segment increased technology spending: 55% of researchers and 78% of analytics report increases; analytics are nearly twice as likely to report significant increases (27% vs. 14%). Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (BRAND: RESEARCH) Increase About the same Decrease 20A (Aggregate, n = 281) 44% 47% 9% 21A (Aggregate, n = 257) 41% 44% 15% 22A (Aggregate, n = 236) 44% 49% 8% 23A (Research, n = 204) 49% 43% 8% 24A (Research, n = 175) 47% 45% 8% 25A (Research, n = 194) 46% 41% 12% 26A (Research, n = 163) 55% 38% 7% Takeaway: Technology spending increases among brand-side researchers peaked at 55% in 26A; decreases were also at their low of 7%. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (BRAND: ANALYTICS) Increase About the same Decrease 23A (n = 175) 61% 32% 7% 24A (n = 186) 58% 31% 11% 25A (n = 173) 67% 29% 4% 26A (n = 151) 77% 18% 4% Takeaway: Technology spending increases among brand-side analytics professionals peaked at 77% in 26A, up from 67% in 25A, while decreases remained low. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: BRAND SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Research (n = 172) 3% 23% 44% 24% 6% Analytics (n = 150) 5% 35% 51% 9% 0% Takeaway: Brand-side analytics professionals report more staff size increases than researchers, 40% to 26%; none in analytics report significant decreases vs. 6% for researchers. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (BRAND: RESEARCH) Increase About the same Decrease 20A (Aggregate, n = 285) 28% 49% 23% 21A (Aggregate, n = 267) 24% 54% 22% 22A (Aggregate, n = 245) 31% 53% 16% 23A (Research, n = 207) 34% 53% 14% 24A (Research, n = 183) 30% 52% 18% 25A (Research, n = 197) 21% 61% 18% 26A (Research, n = 172) 26% 44% 30% Takeaway: Staff size decreases among brand-side researchers peaked at 30% in 26A, up from 18% in 25A and just 14% in 23A. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (BRAND: ANALYTICS) Increase About the same Decrease 23A (n = 174) 45% 43% 12% 24A (n = 190) 46% 41% 13% 25A (n = 172) 36% 47% 17% 26A (n = 150) 40% 51% 9% Takeaway: Staff size increases among brand-side analytics professionals recovered from a -10% drop 36% in 25A to 40% in 26A; decreases fell from 17% to a low of 9%. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: BRAND SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Research (n = 169) 5% 16% 52% 21% 6% Analytics (n = 148) 7% 33% 51% 6% 3% Takeaway: Brand-side analytics professionals are more likely than researchers to be increasing outsourcing (40% vs. 21%) and less likely to be decreasing it (9% vs. 27%). Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (BRAND: RESEARCH) Increase About the same Decrease 23A (n = 206) 27% 59% 14% 24A (n = 179) 22% 58% 20% 25A (n = 196) 22% 59% 19% 26A (n = 169) 21% 52% 26% Takeaway: Outsourcing decreases among brand-side researchers peaked at 26% in 26A; increases remained in the low 20%s (21%) for the third straight year. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (BRAND: ANALYTICS) Increase About the same Decrease 23A (n = 172) 41% 42% 17% 24A (n = 186) 35% 45% 20% 25A (n = 171) 31% 53% 16% 26A (n = 148) 40% 51% 9% Takeaway: Outsourcing increases among brand-side analytics professionals rebounded from a low of 31% in 25A to 40% in 26A; decreases fell from 16% to a low of 9%. Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE, SPENDING, AND STAFFING TRENDS | SUPPLIER POV [DATA] KEY TRENDS INDICES: SUPPLIER SEGMENT Tech-led Service-led: ≤20 FTE Service-led: 21-100 FTE Service-led: 101-500 FTE Service-led: 500+ FTE Revenue 62.5 6.1 42.4 58.9 36.4 Insights staff size 38.7 1.1 27.5 26.8 0.6 Technology spending 96.6 39.0 73.3 100.2 114.7 Darker green indicates higher percentage; yellowish, middle percentage; and darker red, lower percentage. Takeaway: Revenue trends are healthiest among tech-led suppliers (62.5 index) and service-led with 101-500 FTE (58.9), and staff size trends are anemic but healthiest among tech-led (38.7). In each supplier segment, tech spending is the healthiest trend, from 39.0 for service-led with ≤20 FTE to 114.7 for those with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook. REVENUE TREND: SUPPLIER SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Tech-led (n = 38) 23% 35% 24% 18% 0% Service-led: ≤20 FTE (n = 155) 9% 28% 34% 17% 12% Service-led: 21-100 FTE (n = 76) 17% 37% 20% 22% 3% Service-led: 101-500 FTE (n = 55) 23% 36% 22% 15% 4% Service-led: 500+ FTE (n = 48) 5% 46% 32% 14% 3% Takeaway: Revenue increases are most common among tech-led (58%) and 101–500 FTE service-led suppliers (59%); ≤20 FTE service-led suppliers have the weakest revenue trend, as 37% report increases while 29% report decreases. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: SUPPLIER SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Tech-led (n = 37) 28% 44% 26% 3% 0% Service-led: ≤20 FTE (n = 152) 9% 32% 50% 7% 2% Service-led: 21-100 FTE (n = 76) 16% 50% 25% 7% 1% Service-led: 101-500 FTE (n = 51) 24% 51% 24% 0% 0% Service-led: 500+ FTE (n = 50) 33% 49% 18% 0% 0% Takeaway: Technology spending increases range from 41% for service-led with ≤20 FTE to 82% with 500+FTE; decreases range from 0% for service-led suppliers with more than 100 FTE to 9% for those with ≤20 FTE. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: SUPPLIER SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Tech-led (n = 39) 18% 27% 33% 20% 2% Service-led: ≤20 FTE (n = 155) 6% 9% 69% 13% 4% Service-led: 21-100 FTE (n = 77) 14% 34% 26% 17% 9% Service-led: 101-500 FTE (n = 55) 13% 29% 37% 11% 9% Service-led: 500+ FTE (n = 52) 7% 21% 42% 26% 4% Takeaway: Staffing growth is most common among tech-led suppliers (45%), service-led with 21–100 FTE (48%), and with 101–500 FTE (42%); decreases are most common among those with 500+ FTE (30%) and with 21 to 100 FTE (26%). Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: SUPPLIER SEGMENT Increased significantly Increased slightly About the same Decreased slightly Decreased significantly Tech-led (n = 36) 2% 26% 49% 15% 9% Service-led: ≤20 FTE (n = 151) 2% 18% 63% 12% 6% Service-led: 21-100 FTE (n = 70) 9% 12% 59% 15% 5% Service-led: 101-500 FTE (n = 52) 0% 17% 69% 12% 2% Service-led: 500+ FTE (n = 50) 5% 20% 48% 20% 7% Takeaway: Outsourcing increases are most common among tech-led suppliers (28%) and service-led with 500+ FTE (25%); decreases are also most common among these two segments, 27% of service-led with 500+ FTE and 24% of tech-led. Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE, SPENDING, AND STAFFING TRENDS | TECH-LED POV [DATA] KEY TRENDS INDICES: GRIT WAVE (TECH-LED) Revenue Insights staff size Technology spending 20A 75.0 57.0 86.8 21A 70.6 49.3 70.6 22A 113.6 91.7 109.7 23A 108.6 112.9 118.6 24A 60.0 6.8 68.1 25A 98.2 43.6 97.4 26A 62.5 38.7 96.6 Takeaway: Revenue weakened among tech-led suppliers (index dropped from 98.2 to 62.5) as did staff size trends (43.6 to 38.7); technology spending remained about the same (97.4 to 96.6). Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE TREND: GRIT WAVE (TECH-LED) Increase About the same Decrease 20A (n = 92) 62% 22% 16% 21A (n = 68) 63% 16% 21% 22A (n = 154) 79% 10% 11% 23A (n = 69) 72% 16% 11% 24A (n = 57) 58% 25% 17% 25A (n = 51) 73% 13% 14% 26A (n = 38) 58% 24% 18% Takeaway: Tech-led revenue increases declined from 73% in 25A to match its low of 58%, set in the 24A; decreases edged up from 14% to 18%. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (TECH-LED) Increase About the same Decrease 20A (n = 91) 64% 33% 3% 21A (n = 68) 59% 31% 10% 22A (n = 155) 76% 19% 5% 23A (n = 66) 82% 18% 0% 24A (n = 54) 56% 37% 7% 25A (n = 49) 71% 26% 2% 26A (n = 37) 72% 26% 3% Takeaway: Technology spending increases among tech-led suppliers held at 72% in 26A, essentially unchanged from 71% in 25A; decreases remain very low at 3%. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (TECH-LED) Increase About the same Decrease 20A (n = 93) 53% 32% 15% 21A (n = 69) 54% 28% 19% 22A (n = 157) 69% 17% 15% 23A (n = 70) 73% 23% 4% 24A (n = 59) 31% 44% 25% 25A (n = 52) 49% 33% 18% 26A (n = 39) 45% 33% 22% Takeaway: Staff size increases among tech-led suppliers declined somewhat from 49% in 25A to 45% in 26A, while decreases edged up from 18% to 22%. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (TECH-LED) Increase About the same Decrease 22A (n = 132) 30% 56% 14% 23A (n = 63) 26% 70% 4% 24A (n = 57) 20% 67% 13% 25A (n = 45) 32% 51% 17% 26A (n = 36) 28% 49% 23% Takeaway: Outsourcing increases among tech-led suppliers slid from 32% in 25A to 28%, while deceases peaked at 23%, up from 17% in 25A and 10% higher than 24A. Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE, SPENDING, AND STAFFING TRENDS | SERVICE-LED: 500+ FTE POV [DATA] KEY TRENDS INDICES: GRIT WAVE (SERVICE-LED: 500+ FTE) Revenue Insights staff size Technology spending 20A 80.6 31.1 84.3 21A -31.9 -50.4 18.9 22A 127.6 83.9 113.4 23A 128.0 106.9 87.7 24A 36.9 14.5 52.1 25A 35.9 0.7 64.8 26A 36.4 0.6 114.7 Takeaway: The technology spending index for service-led suppliers with 500+ FTE surged to 114.7 in 26A, its highest level since 22A; revenue (36.4) and staff size (0.6) indices have been weak and flat since 24A. Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE TREND: GRIT WAVE (SERVICE-LED: 500+ FTE) Increase About the same Decrease 20A (n = 103) 65% 24% 11% 21A (n = 116) 26% 17% 57% 22A (n = 152) 87% 11% 2% 23A (n = 89) 88% 11% 1% 24A (n = 99) 55% 18% 26% 25A (n = 92) 53% 25% 23% 26A (n = 48) 51% 32% 17% Takeaway: Revenue increases among service-led suppliers with 500+ FTE remained sluggish, 53% in 25A to 51% in 26A, while decreases fell from 23% to 17%. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (SERVICE-LED: 500+ FTE) Increase About the same Decrease 20A (n = 102) 66% 27% 7% 21A (n = 111) 43% 28% 29% 22A (n = 149) 78% 21% 1% 23A (n = 85) 64% 36% 0% 24A (n = 91) 54% 34% 12% 25A (n = 90) 56% 35% 9% 26A (n = 50) 82% 18% 0% Takeaway: Technology spending increases service-led suppliers with 500+ FTE jumped from 56% in 25A to 82% in 26A, highest in the tracked period; decreases fell to zero. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (SERVICE-LED: 500+ FTE) Increase About the same Decrease 20A (n = 103) 48% 25% 27% 21A (n = 113) 19% 19% 61% 22A (n = 155) 66% 24% 10% 23A (n = 93) 82% 15% 3% 24A (n = 102) 43% 26% 32% 25A (n = 91) 36% 31% 33% 26A (n = 55) 28% 42% 30% Takeaway: Staff size increases among service-led suppliers with 500+ FTE declined from 36% in 25A to 28% in 26A, their lowest level since 21A; decreases (30%) outnumbered increases. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (SERVICE-LED: 500+ FTE) Increase About the same Decrease 22A (n = 144) 37% 50% 13% 23A (n = 82) 25% 55% 20% 24A (n = 89) 36% 39% 25% 25A (n = 86) 19% 58% 23% 26A (n = 50) 25% 48% 27% Takeaway: Outsourcing levels among service-led suppliers with 500+ FTE edged up from 19% in 25A to 25% in 26A, but still lagged deceases (27%). Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE, SPENDING, AND STAFFING TRENDS | SERVICE-LED: 101-500 FTE POV [DATA] KEY TRENDS INDICES: GRIT WAVE (SERVICE-LED: 101-500 FTE) Revenue Insights staff size Technology spending 20A 70.5 45.7 69.6 21A -40.2 -43.8 33.3 22A 114.2 91.3 81.0 23A 98.5 92.1 51.3 24A 38.5 17.6 53.3 25A 70.1 43.6 71.6 26A 58.9 26.8 100.2 Takeaway: The technology spending index among service-led suppliers with 101–500 FTE peaked at 100.2 in 26A; revenue (70.1 to 58.9) and staff size (43.6 to 26.8) indices fell. Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE TREND: GRIT WAVE (SERVICE-LED: 101-500 FTE) Increase About the same Decrease 20A (n = 105) 64% 19% 17% 21A (n = 112) 23% 24% 53% 22A (n = 169) 79% 13% 8% 23A (n = 98) 81% 12% 8% 24A (n = 104) 56% 15% 28% 25A (n = 83) 63% 24% 14% 26A (n = 55) 59% 22% 19% Takeaway: Revenue increases among service-led suppliers with 101–500 FTE declined slightly from 63% in 25A to 59% in 26A, while decreases grew from 14% to 19%. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (SERVICE-LED: 101-500 FTE) Increase About the same Decrease 20A (n = 102) 53% 42% 5% 21A (n = 108) 41% 44% 15% 22A (n = 163) 68% 27% 5% 23A (n = 95) 48% 47% 5% 24A (n = 104) 55% 36% 9% 25A (n = 79) 60% 35% 5% 26A (n - 51) 76% 24% 0% Takeaway: Technology spending increases among service-led suppliers with 101–500 FTE grew from 60% in 25A, peaking at 76% in 26A; decreases fell to zero for the first time. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (SERVICE-LED: 101-500 FTE) Increase About the same Decrease 20A (n = 105) 49% 34% 17% 21A (n = 112) 18% 30% 52% 22A (n = 172) 67% 24% 9% 23A (n = 100) 68% 27% 5% 24A (n = 106) 41% 30% 29% 25A (n = 84) 49% 34% 18% 26A (n = 55) 42% 37% 20% Takeaway: Staff size increases among service-led suppliers with 101–500 FTE declined from 49% in 25A to 42% in 26A, while decreases inched up from 18% to 20%. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (SERVICE-LED: 101-500 FTE) Increase About the same Decrease 22A (n = 166) 39% 50% 11% 23A (n = 96) 24% 62% 14% 24A (n = 100) 32% 47% 22% 25A (n = 77) 22% 59% 19% 26A (n = 52) 17% 69% 14% Takeaway: Outsourcing increases among service-led suppliers with 101–500 FTE fell from 22% in 25A to 17% in 26A, but decreases also fell from 19% to 14% Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE, SPENDING, AND STAFFING TRENDS | SERVICE-LED: 21-100 FTE POV [DATA] KEY TRENDS INDICES: GRIT WAVE (SERVICE-LED: 21-100 FTE) Revenue Insights staff size Technology spending 20A 71.2 50.6 80.1 21A -5.4 5.3 39.0 22A 99.5 67.5 71.6 23A 92.3 69.6 70.5 24A 55.3 41.4 51.6 25A 52.9 25.3 54.3 26A 42.4 27.5 73.3 Takeaway: Among service-led suppliers with 21 to 100 FTE, technology spending (73.3) recovered to its highest level since 23A in 26A, while revenue (42.4) fell from 52.9 in 25A and staff size (27.5) remained about the same (25.3). Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE TREND: GRIT WAVE (SERVICE-LED: 21-100 FTE) Increase About the same Decrease 20A (n = 163) 60% 25% 15% 21A (n = 166) 36% 21% 43% 22A (n = 186) 74% 14% 12% 23A (n = 175) 74% 17% 9% 24A (n = 151) 60% 21% 20% 25A (n = 124) 60% 21% 19% 26A (n = 76) 54% 20% 25% Takeaway: Revenue increases among service-led suppliers with 21–100 FTE declined from 60% in 25A to 54% in 26A, while decreases grew from 19% to 25%. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (SERVICE-LED: 21-100 FTE) Increase About the same Decrease 20A (n = 161) 61% 34% 5% 21A (n = 166) 47% 34% 32% 22A (n = 183) 61% 35% 4% 23A (n = 172) 59% 37% 5% 24A (n = 150) 48% 42% 10% 25A (n = 126) 50% 39% 11% 26A (n = 76) 66% 25% 8% Takeaway: Technology spending increases among service-led suppliers with 21–100 FTE grew from 50% in 25A to 66% in 26A, the highest level since 22A; decreases slipped from 11% to 8%. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (SERVICE-LED: 21-100 FTE) Increase About the same Decrease 20A (n = 164) 53% 27% 20% 21A (n = 170) 34% 34% 32% 22A (n = 191) 59% 27% 14% 23A (n = 180) 65% 21% 13% 24A (n = 155) 48% 33% 19% 25A (n = 130) 44% 34% 22% 26A (n = 77) 48% 26% 26% Takeaway: Staff size increases among service-led with 21–100 FTE rose to 48% in 26A, up from 44% in 25A, while decreases grew from 22% to 26%. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (SERVICE-LED: 21-100 FTE) Increase About the same Decrease 22A (n = 186) 33% 56% 10% 23A (n = 169) 33% 54% 13% 24A (n = 151) 26% 55% 19% 25A (n = 121) 22% 60% 18% 26A (n = 70) 21% 59% 20% Takeaway: Outsourcing increases among service-led suppliers with 21–100 FTE suppliers were about the same in 26A (21%) as in 25A (22%) as were decreases (20% and 18%). Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE, SPENDING, AND STAFFING TRENDS | SERVICE-LED: ≤20 FTE POV [DATA] KEY TRENDS INDICES: GRIT WAVE (SERVICE-LED: ≤20 FTE) Revenue Insights staff size Technology spending 20A 26.9 12.5 40.2 21A -44.9 -17.0 13.2 22A 38.9 13.0 29.5 23A 51.4 24.2 32.2 24A 17.6 10.8 29.0 25A 15.1 6.0 30.4 26A 6.1 1.1 39.0 Takeaway: Among service-led suppliers with ≤20 FTE, the revenue trend index declined from 16.1 in 25A to 6.1 in 26A, and the staff size index slid from 6.0 to 1.1. The tech spending trend strengthened slightly from 30.4 in 25A to 39.0 in 26A. Source: GRIT 2026 Insights Practice Report, Greenbook REVENUE TREND: GRIT WAVE (SERVICE-LED: ≤20 FTE) Increase About the same Decrease 20A (n = 305) 46% 29% 26% 21A (n = 283) 28% 18% 54% 22A (n = 303) 55% 19% 25% 23A (n = 263) 58% 23% 19% 24A (n = 189) 46% 25% 29% 25A (n = 221) 44% 24% 32% 26A (n = 155) 37% 34% 28% Takeaway: Revenue increases among service-led suppliers with ≤20 FTE fell from 44% in 25A to 37% in 26A, while decreases declined from 32% to 28%. Source: GRIT 2026 Insights Practice Report, Greenbook TECH SPENDING TREND: GRIT WAVE (SERVICE-LED: ≤20 FTE) Increase About the same Decrease 20A (n = 301) 43% 46% 11% 21A (n = 280) 38% 40% 23% 22A (n = 305) 39% 48% 13% 23A (n = 264) 35% 57% 9% 24A (n = 190) 37% 51% 12% 25A (n = 220) 39% 50% 11% 26A (n = 152) 41% 50% 9% Takeaway: Technology spending increases among service-led suppliers with ≤20 FTE have slowly rebounded from a low of 35% in 23A to 41% in 26A, and decreases have matched 23A’s all-time low of 9%. Source: GRIT 2026 Insights Practice Report, Greenbook STAFF SIZE TREND: GRIT WAVE (SERVICE-LED: ≤20 FTE) Increase About the same Decrease 20A (n = 305) 27% 58% 15% 21A (n = 282) 16% 57% 27% 22A (n = 308) 23% 63% 14% 23A (n = 265) 28% 63% 9% 24A (n = 193) 24% 61% 15% 25A (n = 218) 23% 61% 17% 26A (n = 155) 15% 69% 16% Takeaway: Staff size increases among service-led suppliers with ≤20 FTE fell to 15% in 26A, their lowest level in the tracked period; decreases held at 16% compared to 17% in 25A. Source: GRIT 2026 Insights Practice Report, Greenbook OUTSOURCING TREND: GRIT WAVE (SERVICE-LED: ≤20 FTE) Increase About the same Decrease 22A (n = 296) 27% 62% 10% 23A (n = 263) 25% 63% 12% 24A (n = 182) 18% 68% 14% 25A (n = 214) 17% 63% 19% 26A (n = 151) 20% 63% 18% Takeaway: Outsourcing increases among service-led suppliers with ≤20 FTE inched up from 17% in 25A to 20% in 26A while decreases stayed about the same (from 19% to 18%). Source: GRIT 2026 Insights Practice Report, Greenbook THE BIG PICTURE [STRATEGIC INTERPRETATION] For the first time, Business Outlook is broken out by service-led size band, yielding a clearer economic picture of the industry — and each segment occupies a distinct situation. Tech-led suppliers, who thrived through the pandemic, were undercut when mass-market generative AI met needs they had expected to fill; with revenue soft but technology spending strong for two years, they appear to be reloading toward industry-specific, workflow-integrated infrastructure a general-purpose model cannot supplant. Among service-led suppliers, those with 500+ FTE show three years of flat revenue growth and stagnant staffing alongside a technology-spending high, consistent with a deliberate repositioning toward consulting and analytics. Those with 101–500 FTE are thriving, leading service-led revenue growth with technology and staffing both expanding. Those with 21–100 FTE are less settled, leaning on technology and outsourcing to avoid fixed costs, while those with ≤20 FTE post low metrics that partly reflect a segment structurally bounded by its own definition yet resilient across every wave. On the brand side, the divergence between research and analytics is the section’s starkest finding: analytics professionals are expanding on every tracked dimension (those with budgets over $15MM grew from 26% to 40% since 23A) while researchers face falling project spending, net-negative staffing growth, and contracting outsourcing. A genuine disconnect persists between holding brand budgets and softening supplier revenue that the directional data cannot fully resolve. One finding holds across every segment without exception: technology spending is strong — participants disagree about their destinations but agree on how they intend to get there. Full analysis and supporting data: GRIT 2026 Insights Practice Report. Mood & Confidence This section looks at optimism about the future of roles, companies, and the industry plus performance against insights goals from the perspectives of brand-side research and analytics professionals as well as service-led suppliers across size bands and tech-led suppliers. WHAT ARE THE REASONS TO BE CHEERFUL? [ORIENTATION] OPTIMISM ABOUT DEPARTMENT OR ROLE [BRAND]/COMPANY [SUPPLIER]: GRIT SEGMENT Very Optimistic Optimistic Neutral Pessimistic Very Pessimistic Research (n = 176) 19% 50% 19% 8% 4% Analytics (n = 152) 31% 52% 12% 4% 1% Tech-led (n = 39) 33% 54% 7% 6% 0% Service-led: 500+ FTE (n = 55) 18% 31% 33% 16% 2% Service-led: 101-500 FTE (n = 56) 21% 63% 11% 5% 0% Service-led: 21-100 FTE (n = 78) 29% 35% 28% 7% 1% Service-led: ≤20FTE (n = 157) 17% 45% 20% 15% 3% Takeaway: Brand-side analytics professionals (83% to 5%), tech-led suppliers (87% to 6%), and service-led suppliers with 101 to 500 FTE (84% to 5%) are the most optimistic about their situations, overall. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT SEGMENT Exceeded significantly Exceeded slightly Met our goals Fell slightly short Fell significantly short Research (n = 176) 13% 31% 35% 18% 4% Analytics (n = 152) 10% 29% 49% 11% 0% Tech-led (n = 39) 15% 29% 36% 20% 0% Service-led: 500+ FTE (n = 158) 2% 18% 53% 23% 4% Service-led: 101-500 FTE (n = 56) 16% 32% 24% 20% 8% Service-led: 21-100 FTE (n = 79) 14% 19% 34% 28% 5% Service-led: ≤20FTE (n = 158) 9% 18% 35% 20% 17% Takeaway: Brand-side analytics professionals (39% to 11%), tech-led suppliers (44% to 20%), and brand-side researchers (44% to 22%) have the best ratios of exceeding goals to falling short of them. Source: GRIT 2026 Insights Practice Report, Greenbook GOAL PERFORMANCE AND OPTIMISM | BRAND POV [DATA] PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: BRAND SEGMENT Exceeded significantly Exceeded slightly Met our goals Fell slightly short Fell significantly short Research (n = 176) 13% 31% 35% 18% 4% Analytics (n = 152) 10% 29% 49% 11% 0% Takeaway: Among brand-side analytics professionals, 39% exceeded goals vs. 44% for researchers, but analytics have a much lower “fell short” rate (11% vs. 22%) and no significant shortfalls. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (BRAND: RESEARCH) Exceeded goals Met goals Fell short of goals 20A (Aggregate, n = 298) 37% 45% 18% 21A (Aggregate, n = 274) 39% 42% 19% 22A (Aggregate, n = 254) 40% 46% 15% 23A (Aggregate, n = 214) 38% 47% 15% 24A (Research, n = 191) 39% 43% 19% 25A (Research, n = 202) 44% 41% 15% 26A (Research, n = 176) 44% 35% 22% Takeaway: Brand-side researchers exceeding goals held at 44% in 26A, matching 25A as the highest in the series, but “fell short” rose to 22%. Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (BRAND: ANALYTICS) Exceeded goals Met goals Fell short of goals 23A (n = 183) 40% 43% 17% 24A (n = 194) 33% 44% 23% 25A (n = 177) 34% 55% 11% 26A (n = 152) 39% 49% 12% Takeaway: Among brand-side analytics professionals, those exceeding goals grew from 34% to 39% while those falling short remained near last year’s low (12% versus 11%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: BRAND SEGMENT Very Optimistic Optimistic Neutral Pessimistic Very Pessimistic Research (n = 176) 19% 50% 19% 8% 4% Analytics (n = 152) 31% 52% 12% 4% 1% Takeaway: Brand-side analytics professionals are more optimistic about their department or role than researchers (83% vs. 69%), with many more describing themselves as very optimistic (31% vs. 19%); pessimism is more than twice as high among researchers (12% vs. 5%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: GRIT WAVE (BRAND: RESEARCH) Optimistic Neutral Pessimistic 20A (Aggregate, n = 135) 70% 19% 10% 21A (Aggregate, n = 270) 69% 22% 9% 22A (Aggregate, n = 253) 79% 14% 6% 23A (Aggregate, n = 214) 75% 18% 7% 24A (Research, n = 191) 76% 19% 5% 25A (Research, n = 201) 69% 21% 9% 26A (Research, n =176) 70% 19% 12% Takeaway: Brand-side researcher optimism about their role the past two years has been 69-70%, same as it was prior to peaking at 79% in 22A; at 12%, pessimism is the highest in the tracked period. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: GRIT WAVE (BRAND: ANALYTICS) Optimistic Neutral Pessimistic 23A (n = 183) 85% 8% 7% 24A (n = 194) 82% 11% 7% 25A (n = 177) 88% 10% 2% 26A (n = 152) 83% 12% 5% Takeaway: Brand-side analytics professionals’ optimism about their role has been consistently above 80% across all waves (82–88%); pessimism remains in the single digits (2–7%) throughout. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: BRAND SEGMENT Very Optimistic Optimistic Neutral Pessimistic Very Pessimistic Research (n = 176) 20% 54% 21% 5% 0% Analytics (n = 152) 30% 58% 9% 3% 1% Takeaway: Both brand segments are optimistic about the industry (74% research, 88% analytics), but analytics professionals are notably more likely to be very optimistic (30% vs. 20%); pessimism is low in both segments (5% research, 4% analytics). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (BRAND: RESEARCH) Optimistic Neutral Pessimistic 20A (Aggregate, n = 139) 73% 18% 9% 21A (Aggregate, n = 274) 79% 15% 6% 22A (Aggregate, n = 253) 87% 11% 2% 23A (Aggregate, n = 214) 83% 13% 4% 24A (Research, n = 191) 83% 14% 3% 25A (Research, n = 202) 75% 18% 8% 26A (Research, n = 176) 74% 21% 6% Takeaway: Coming out of the pandemic, brand-side researchers’ industry optimism peaked at 87% in 22A but has declined to 74% in 26A, its lowest since 20A; at 6%, pessimism remains low but has doubled from 3% over two years. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (BRAND: ANALYTICS) Optimistic Neutral Pessimistic 23A (n = 183) 88% 10% 2% 24A (n = 194) 85% 11% 5% 25A (n = 177) 89% 8% 3% 26A (n = 152) 88% 9% 4% Takeaway: Brand-side analytics professionals’ industry optimism has been consistently in the upper-80%s (85–89%) across all tracked waves; at 88%, 26A is virtually unchanged from 25A while pessimism remains minimal (4%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM & IDENTITY | BRAND POV [DATA] OPTIMISM ABOUT DEPARTMENT OR ROLE: DEPARTMENT/FUNCTIONAL AREA (BRAND) Optimistic Not Optimistic Marketing/brand/communications (n = 37) 86% 14% Executive team (n = 24) 85% 15% Analytics/Data Science (n = 86) 83% 17% Product/CX/UX/innovation/R&D (n = 39) 72% 28% Insights or research group (n = 130) 68% 32% Takeaway: On the brand-side, optimism is highest for those working in marketing/brand/communications (86%), on the executive team (85%), and in analytics/Data Science (83%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: INSIGHTS STAFF SIZE (BRAND) Optimistic Not Optimistic 4 or fewer (n = 59) 61% 39% 5 to 9 (n = 60) 81% 19% 10 to 19 (n = 67) 66% 34% 20 or more (n = 137) 84% 16% Takeaway: Optimism is lowest when there are only four or fewer insights professionals on staff (61%) and when there are 10 to 19 (66%); it’s highest when there are five to nine (81%) and 20 or more (84%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: MOST IMPORTANT INSIGHTS STAFF ROLE (BRAND) Optimistic Not Optimistic Insights/analytics/research ops (n = 104) 84% 16% Customer/user feedback or VoC (n = 31) 78% 22% Strategic insights consulting (n = 52) 74% 26% In-house data analysis or modeling (n = 71) 74% 26% In-house research provider (n = 54) 70% 30% Takeaway: Brand-side insights professionals are most optimistic about their roles when the primary role of insights staff is insights, analytics, or research operations (84%); optimism is lowest when it’s in-house research provider (70%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: AREAS LED BY INSIGHTS (BRAND) Optimistic Not Optimistic Brand management (n = 55) 96% 4% Product development/innovation (n = 105) 84% 16% Data Science/advanced analytics (n = 146) 84% 16% Business intelligence/reporting (n = 142) 83% 17% Digital UX/web analytics (n = 62) 82% 18% Advertising/communications research (n = 102) 80% 20% Shopper insights (n = 98) 79% 21% Competitive/market intelligence (n = 143) 79% 21% Customer experience (CX) (n = 93) 78% 22% Consumer market insights (n = 170) 75% 25% Takeaway: Brand-side insights professionals are most optimistic about their roles when insights lead brand management (96%), least when they lead consumer market insights (75%). Source: GRIT 2026 Insights Practice Report, Greenbook HIGHEST OPTIMISM ABOUT DEPARTMENT OR ROLE: SPEND SIGNIFICANT TIME (BRAND) Optimistic Not Optimistic Partner/channel selection/optimization (n = 89) 86% 14% Later stage product/service development (n = 147) 81% 19% Brand tracking (n = 108) 81% 19% Digital/online/website experience (n = 115) 79% 21% Advertising, media/campaign performance (n = 113) 79% 21% Takeaway: Brand-side insights professionals are most optimistic about their roles when they spend significant time on partner/channel selection/optimization (86%). Source: GRIT 2026 Insights Practice Report, Greenbook LOWEST OPTIMISM ABOUT DEPARTMENT OR ROLE: SPEND SIGNIFICANT TIME (BRAND) Optimistic Not Optimistic Pricing (n = 102) 77% 23% Shopper behavior/offline experience (n = 87) 77% 23% Market structure/competition/opportunity (n = 163) 77% 23% Customer satisfaction/loyalty/value (n = 153) 75% 25% Early-stage product/service development (n = 160) 74% 26% Brand strategy/positioning (n = 168) 74% 26% Segmentation/audience definition (n = 167) 74% 26% Takeaway: Brand-side insights professionals are least optimistic about their roles when they spend significant time on early-stage product/service development, brand strategy/positioning, and segmentation/audience definition (74% each). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM & MANAGING INSIGHTS | BRAND POV [DATA] OPTIMISM ABOUT DEPARTMENT OR ROLE: OUTSOURCING EXPECTATION (BRAND) Optimistic Not Optimistic Increase (n = 117) 84% 16% Stay about the same (n = 165) 75% 25% Decrease (n = 41) 58% 42% Takeaway: Brand-side insights professionals are more optimistic about the future of their roles when they expect outsourcing to external suppliers to increase (84%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: QUALITATIVE RESEARCH SUPPLIERS (BRAND) Optimistic Not Optimistic Work with regularly (n = 145) 82% 18% Work with occasionally (n = 144) 72% 28% Rarely or never work with (n = 39) 64% 36% Takeaway: Brand-side insights professionals are more optimistic about the future of their roles when they work regularly with qualitative research suppliers (82%) than those who rarely or never do (64%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: STRATEGIC CONSULTANTS (BRAND) Optimistic Not Optimistic Work with regularly (n = 102) 85% 15% Work with occasionally (n = 155) 75% 25% Rarely or never work with (n = 71) 65% 35% Takeaway: Brand-side insights professionals are more optimistic about the future of their roles when they work with them regularly (85%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: USE OF AGENTIC AI (BRAND) Optimistic Not Optimistic Recruiting/sampling/routing participants (n = 36) 94% 6% Monitoring for issues and alerts (n = 71) 83% 17% Running surveys/interviews/etc. (n = 48) 80% 20% Preparing and integrating data (n = 99) 78% 22% Creating/updating deliverables (n = 105) 77% 23% Analyzing or modeling data (n = 114) 73% 27% Selecting /shortlisting suppliers/partners (n = 33) 73% 27% Takeaway: Brand-side insights professionals are least optimistic about their roles when their organizations use agentic AI for recruiting/sampling/routing participants (94%), monitoring for issues and alerts (83%), and running surveys/interviews/etc. (80%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: GUIDELINES FOR AI USE (BRAND) Optimistic Not Optimistic Yes (n = 158) 79% 21% No, just some informal ones (n = 125) 76% 24% No, none at all (n = 39) 60% 40% Takeaway: On the brand side, optimism about their roles does not differ according to whether they have formal (79%) or informal guidelines for use of AI in insights work (76%); however, it plummets if there are no guidelines (60%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: CLARITY OF EXPECTATIONS FOR AI USE (BRAND) Optimistic Not Optimistic Completely or mostly clear (n = 151) 83% 17% Somewhat/not very/not at all clear (n = 174) 70% 30% Takeaway: Establishing clear expectations of how AI should be used insights work can improve optimism (83%) about the future of brand-side insights roles. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: ANNUAL BUDGET (BRAND) Optimistic Not Optimistic Under $1MM 70% 30% $1MM to $15MM 81% 19% More than $15MM 83% 17% Takeaway: Brand-side insights professionals are most optimistic about their roles when their research budgets exceed $1MM (more than 80%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: INCREASES (BRAND) Optimistic Not Optimistic Spending on research projects (n = 149) 90% 10% Spending on technology (n = 208) 82% 18% Number of FTE positions (n = 112) 92% 8% Work by suppliers vs. in-house (n = 97) 92% 8% Takeaway: Brand-side researchers are extremely optimistic about their roles when research spending (90%), technology spending (82%), FTE staff (92%), and outsourcing (92%) increase. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: DECREASES (BRAND) Optimistic Not Optimistic Spending on research projects (n = 60) 58% 42% Spending on technology (n = 16) 51% 49% Number of FTE positions (n = 60) 48% 52% Work by suppliers vs. in-house (n = 52) 62% 38% Takeaway: Brand-side researchers are much less optimistic about their roles when research spending (58%), technology spending (51%), FTE staff (48%), and outsourcing (62%) decrease. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT DEPARTMENT OR ROLE: PERFORMANCE AGAINST GOALS (BRAND) Optimistic Not Optimistic Exceeded (n = 138) 89% 11% Met (n = 132) 78% 22% Fell slightly short (n = 58) 38% 62% Takeaway: Brand-side insights professionals are more optimistic about their roles when their organizations exceed their goals (89%) than when goals are met (78%) and especially than when they fall short (38%). Source: GRIT 2026 Insights Practice Report, Greenbook GOAL PERFORMANCE AND OPTIMISM | SUPPLIER POV�[DATA] PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: SUPPLIER SEGMENT Exceeded significantly Exceeded slightly Met our goals Fell slightly short Fell significantly short Tech-led (n = 39) 15% 29% 36% 20% 0% Service-led: ≤20FTE (n = 158) 9% 18% 35% 20% 17% Service-led: 21-100 FTE (n = 79) 14% 19% 34% 28% 5% Service-led: 101-500 FTE (n = 56) 16% 32% 24% 20% 8% Service-led: 500+ FTE (n = 55) 2% 18% 53% 23% 4% Takeaway: More than 40% of service-led suppliers with 101 to 500 FTE (47%) and tech-led suppliers (44%) exceeded goals, compared to only 33% of those with 21 to 100 FTE, 27% of those with ≤20 FTE, and 21% of those with 500+ FTE. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: SUPPLIER SEGMENT Very Optimistic Optimistic Neutral Pessimistic Very Pessimistic Tech-led (n = 39) 33% 54% 7% 6% 0% Service-led: ≤20FTE (n = 157) 17% 45% 20% 15% 3% Service-led: 21-100 FTE (n = 78) 29% 35% 28% 7% 1% Service-led: 101-500 FTE (n = 56) 21% 63% 11% 5% 0% Service-led: 500+ FTE (n = 55) 18% 31% 33% 16% 2% Takeaway: Tech-led (87%) and 101–500 FTE service-led (84%) suppliers show the highest company optimism while fewer than half of service-led with 500+ FTE are optimistic (49%); for service-led with ≤20 FTE and those with 500+ FTE (18% each), company pessimism is more than double any other supplier segment. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: SUPPLIER SEGMENT Very Optimistic Optimistic Neutral Pessimistic Very Pessimistic Tech-led (n = 39) 26% 37% 29% 7% 2% Service-led: ≤20FTE (n = 157) 7% 44% 26% 20% 3% Service-led: 21-100 FTE (n = 79) 18% 44% 26% 10% 2% Service-led: 101-500 FTE (n = 56) 13% 48% 32% 6% 0% Service-led: 500+ FTE (n = 55) 17% 43% 20% 21% 0% Takeaway: Tech-led (+24%) and 101–500 FTE service-led (+23%) suppliers have much more optimism about their companies than about the industry; industry pessimism exceeds 20% for service-led with ≤20 FTE (23%) and those with 500+ FTE (21%). Source: GRIT 2026 Insights Practice Report, Greenbook PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (TECH-LED) Exceeded goals Met goals Fell short of goals 20A (n = 97) 34% 39% 27% 21A (n = 69) 52% 22% 26% 22A (n = 163) 55% 27% 18% 23A (n = 70) 34% 39% 27% 24A (n = 61) 33% 34% 33% 25A (n = 53) 45% 33% 23% 26A (n = 39) 44% 36% 20% Takeaway: While recovering from the pandemic in 22A, tech-led suppliers who exceeded goals peaked at 55% before plunging to 34% in 23A; now, more are exceeding goals (44%) than had been going into the pandemic (34%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: GRIT WAVE (TECH-LED) Optimistic Neutral Pessimistic 20A (n = 41) 88% 7% 5% 21A (n = 69) 91% 6% 3% 22A (n = 162) 88% 8% 4% 23A (n = 70) 84% 12% 3% 24A (n = 61) 84% 13% 3% 25A (n = 53) 78% 22% 0% 26A (n = 39) 87% 7% 6% Takeaway: Tech-led suppliers were the only segment to thrive during the pandemic, with optimism about their companies peaking at 91% in 21A; since then, it had gradually declined to 78% last year before rebounding to 87% this year. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (TECH-LED) Optimistic Neutral Pessimistic 20A (n = 41) 68% 27% 5% 21A (n = 69) 87% 9% 4% 22A (n = 163) 90% 9% 2% 23A (n = 70) 85% 13% 1% 24A (n = 61) 85% 12% 4% 25A (n = 53) 79% 7% 15% 26A (n = 39) 62% 29% 8% Takeaway: Industry optimism from tech-led suppliers tumbled from 79% in 25A to 62% in 26A, the lowest in the tracked period. Source: GRIT 2026 Insights Practice Report, Greenbook GOAL PERFORMANCE AND OPTIMISM | SERVICE-LED: 500+ FTE POV [DATA] PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (SERVICE-LED: 500+ FTE) Exceeded goals Met goals Fell short of goals 20A (n = 106) 42% 37% 21% 21A (n = 119) 38% 27% 35% 22A (n = 160) 68% 28% 4% 23A (n = 97) 59% 25% 16% 24A (n = 104) 34% 42% 24% 25A (n = 98) 32% 33% 35% 26A (n = 55) 21% 53% 27% Takeaway: Service-led suppliers with 500+ FTE who exceeded goals fell from 32% in 25A to 21% in 26A, half the total going into the pandemic. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: GRIT WAVE (SERVICE-LED: 500+ FTE) Optimistic Neutral Pessimistic 20A (n = 58) 67% 21% 12% 21A (n = 119) 76% 13% 10% 22A (n = 160) 91% 8% 1% 23A (n = 97) 84% 9% 7% 24A (n = 104) 74% 16% 10% 25A (n = 98) 76% 7% 17% 26A (n = 55) 49% 33% 17% Takeaway: Company optimism among service-led suppliers with 500+ FTE dropped sharply from 76% last year to 49%, lowest in the tracked period. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (SERVICE-LED: 500+ FTE) Optimistic Neutral Pessimistic 20A (n = 58) 67% 24% 9% 21A (n = 119) 80% 16% 4% 22A (n = 160) 87% 11% 3% 23A (n = 97) 84% 12% 5% 24A (n = 104) 81% 12% 7% 25A (n = 98) 67% 18% 15% 26A (n = 55) 59% 20% 21% Takeaway: Industry optimism among service-led suppliers with 500+ FTE declined from 67% in 25A to 59% in 26A, continuing a multi-wave fall from 87% in 22A; over that period, pessimism has increased seven-fold from 3% to 21%. Source: GRIT 2026 Insights Practice Report, Greenbook GOAL PERFORMANCE AND OPTIMISM | SERVICE-LED: 101-500 FTE POV [DATA] PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (SERVICE-LED: 101-500 FTE) Exceeded goals Met goals Fell short of goals 20A (n = 108) 42% 38% 20% 21A (n = 116) 26% 34% 40% 22A (n = 174) 61% 28% 11% 23A (n = 102) 53% 33% 14% 24A (n = 110) 35% 28% 37% 25A (n = 87) 49% 33% 18% 26A (n = 56) 47% 24% 28% Takeaway: Service-led suppliers with 101–500 FTE exceeding goals declined slightly from 49% in 25A to 47% in 26A, while those falling short grew from 18% to 28%. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: GRIT WAVE (SERVICE-LED: 101-500 FTE) Optimistic Neutral Pessimistic 20A (n = 50) 84% 10% 6% 21A (n = 115) 73% 20% 7% 22A (n = 173) 89% 8% 3% 23A (n = 102) 82% 11% 7% 24A (n = 110) 67% 25% 8% 25A (n = 87) 78% 19% 3% 26A (n = 56) 84% 11% 5% Takeaway: Company optimism among service-led suppliers with 101–500 FTE (84%) continued to increase from 24A’s low point (67%), matching the level going into the pandemic. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (SERVICE-LED: 101-500 FTE) Optimistic Neutral Pessimistic 20A (n = 50) 72% 20% 8% 21A (n = 116) 86% 10% 3% 22A (n = 174) 87% 10% 2% 23A (n = 102) 74% 21% 5% 24A (n = 110) 77% 14% 9% 25A (n = 87) 75% 17% 8% 26A (n = 56) 62% 32% 6% Takeaway: Industry optimism among service-led suppliers with 101–500 FTE fell from 75% in 25A to 62% in 26A, lowest in the tracked period. Source: GRIT 2026 Insights Practice Report, Greenbook GOAL PERFORMANCE AND OPTIMISM | SERVICE-LED: 21-100 FTE POV [DATA] PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (SERVICE-LED: 21-100 FTE) Exceeded goals Met goals Fell short of goals 20A (n = 169) 40% 35% 25% 21A (n = 172) 36% 28% 36% 22A (n = 195) 52% 30% 17% 23A (n = 184) 45% 36% 19% 24A (n = 156) 42% 31% 27% 25A (n = 133) 43% 29% 28% 26A (n = 79) 33% 34% 33% Takeaway: Service-led suppliers with 21–100 FTE exceeding goals fell from 43% in 25A to 33% in 26A, lowest in the tracked period, while those falling short rose from 28% to 33%. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: GRIT WAVE (SERVICE-LED: 21-100 FTE) Optimistic Neutral Pessimistic 20A (n = 74) 72% 19% 9% 21A (n = 171) 72% 20% 8% 22A (n = 195) 86% 11% 4% 23A (n = 184) 84% 13% 3% 24A (n = 155) 73% 16% 10% 25A (n = 133) 74% 19% 7% 26A (n = 78) 64% 28% 8% Takeaway: Company optimism among service-led suppliers with 21–100 FTE declined from 74% in 25A to 64% in 26A, lowest in the tracked period; pessimism held at 8%. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (SERVICE-LED: 21-100 FTE) Optimistic Neutral Pessimistic 20A (n = 75) 64% 21% 15% 21A (n = 172) 72% 16% 13% 22A (n = 194) 85% 11% 4% 23A (n = 184) 82% 11% 7% 24A (n = 156) 76% 19% 5% 25A (n = 133) 67% 23% 10% 26A (n = 79) 62% 26% 12% Takeaway: Industry optimism among service-led suppliers with 21–100 FTE declined from 67% last year to 62% currently, continuing a multi-wave decline from 85% in 22A; pessimism rose slightly from 10% to 12%. Source: GRIT 2026 Insights Practice Report, Greenbook GOAL PERFORMANCE AND OPTIMISM | SERVICE-LED: ≤20 FTE POV [DATA] PERFORMANCE AGAINST RESEARCH AND INSIGHTS/ANALYTICS GOALS: GRIT WAVE (SERVICE-LED: ≤20 FTE) Exceeded goals Met goals Fell short of goals 20A (n = 310) 39% 35% 25% 21A (n = 290) 22% 32% 46% 22A (n = 310) 40% 31% 29% 23A (n = 271) 36% 34% 30% 24A (n = 197) 31% 33% 36% 25A (n = 224) 30% 33% 38% 26A (n = 158) 27% 35% 38% Takeaway: Service-led suppliers with ≤20 FTE have persistently declined in goal performance since 22A: those exceeding goals fell from 40% in 22A to 27% in 26A; those falling short have remained at 38% for two consecutive waves. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: GRIT WAVE (SERVICE-LED: ≤20 FTE) Optimistic Neutral Pessimistic 20A (n = 142) 71% 21% 8% 21A (n = 290) 68% 21% 11% 22A (n = 310) 75% 18% 7% 23A (n = 271) 76% 16% 8% 24A (n = 196) 70% 16% 15% 25A (n = 224) 71% 20% 10% 26A (n = 157) 62% 20% 17% Takeaway: Company optimism among service-led suppliers with ≤20 FTE declined from 71% last year to 62% currently, lowest in the tracked period; pessimism grew from 10% to 17%, also the highest in the series. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT INSIGHTS & ANALYTICS INDUSTRY: GRIT WAVE (SERVICE-LED: ≤20 FTE) Optimistic Neutral Pessimistic 20A (n = 142) 56% 28% 16% 21A (n = 290) 68% 22% 10% 22A (n = 309) 81% 13% 6% 23A (n = 271) 77% 13% 10% 24A (n = 197) 65% 22% 13% 25A (n = 224) 60% 28% 11% 26A (n = 157) 51% 26% 23% Takeaway: Industry optimism among service-led suppliers with ≤20 FTE fell from 60% in 25A to 51% in 26A, lowest level in the tracked period; pessimism more than doubled, from 11% to 23%, highest in the series. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM & IDENTITY | SERVICE-LED SUPPLIER POV�[DATA] OPTIMISM ABOUT COMPANY: DATA COLLECTION SERVICES (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Sampling (n = 158) 64% 36% Moderating/interviewing (n = 215) 63% 37% Recruiting/pre-recruiting (n = 180) 62% 38% Offline quantitative data collection (n = 191) 62% 38% Offline qualitative data collection (n = 194) 61% 39% Interviewing facilities/locations (n = 106) 55% 45% None of the above (n = 58) 76% 24% Takeaway: Service-led suppliers who offer sampling (64%) are more optimistic about their company’s future than those who offer interviewing facilities (55%), but not as optimistic as those who do not offer data collection services (76%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: SIGNIFICANT REVENUE SOURCES (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Technology (n = 60) 81% 19% Qualitative research (n = 137) 74% 26% Strategic consulting (n = 148) 74% 26% Data and analytics (n = 117) 73% 27% Field services (n = 82) 68% 32% Full-service research (n = 249) 62% 38% Takeaway: Service-led suppliers with who earn revenue from technology offerings are the most optimistic about the future of their company (81%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: HIGHEST REVENUE SOURCE (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Strategic consulting (n = 53) 77% 23% Qualitative research (n = 38) 72% 28% Field services (n = 30) 63% 37% Full-service research (n = 190) 60% 40% Data and analytics (n = 27) 56% 44% Takeaway: Those whose defining source of revenue is strategic consulting are the most optimistic about the future of their company (77%) followed by those in qualitative research (72%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: EXPECTED OUTSOURCING TREND (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Increase (n = 101) 73% 27% Stay about the same (n = 192) 64% 36% Decrease (n = 39) 46% 54% Takeaway: Service-led suppliers who expect outsourcing to increase are more optimistic about the future of their own companies (73%) than those who expect it to stay the same (64%) or decrease (46%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: DATA & ANALTYICS SUPPLIERS (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Work with regularly (n = 91) 74% 26% Work with occasionally (n = 135) 58% 42% Rarely or never work with (n = 112) 63% 37% Takeaway: Service-led suppliers who work regularly with data and analytics suppliers are more optimistic about their own company (74%) than those who work with them occasionally (58%) or rarely or never (63%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: QUALITATIVE RESEARCH SUPPLIERS (SERVICE-LED SUPPLIER) OPTIMISM ABOUT COMPANY: SOURCING PARTICIPANTS & DATA (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Automated right amount or too much (n = 70) 79% 21% Automated too little (n = 64) 52% 48% Takeaway: When service-led suppliers think automation is used too little for sourcing participants and data, only 52% are optimistic about their company’s future compared to 79% who believe they use it the right amount or too much. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: EXECUTING FIELDWORK (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Automated right amount or too much (n = 78) 71% 29% Automated too little (n = 66) 58% 42% Takeaway: When service-led suppliers think automation is not used enough for executing fieldwork, only 58% are optimistic about their company’s future compared to 71% of those who think is it used enough or too much. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: PREPARING & INTEGRATING DATA (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Automated right amount or too much (n = 82) 76% 24% Automated too little (n = 72) 57% 43% Takeaway: When service-led suppliers think automation is not used enough for preparing and integrating data, only 57% are optimistic about their company’s future compared to 76% of those who think is it used enough or too much. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: ANALYZING & MODELING (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Automated right amount or too much (n = 88) 76% 24% Automated too little (n = 69) 57% 43% Takeaway: When service-led suppliers think automation is not used enough for analyzing and modeling insights, only 57% are optimistic about their company’s future compared to 76% of those who think is it used enough or too much. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: GUIDELINES FOR AI USE (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Yes (n = 165) 71% 29% No, just some informal ones (n = 128) 59% 41% No, none at all (n = 41) 49% 51% Takeaway: Service-led suppliers are more optimistic about their company’s future when their organization has formal guidelines for AI use in insights (71%) than if they only have informal ones (59%) or none at all (49%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: CLARITY OF EXPECTATIONS FOR AI USE (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Completely or mostly clear (n = 214) 74% 26% Somewhat/not very/not at all clear (n = 118) 48% 52% Takeaway: When expectations for use of AI tools and automation in insights work are completely or mostly clear, 74% of service-led suppliers are optimistic about the future of their company compared to just 48% when they are not. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: CONFIDENCE IN MINIMIZING RISKS OF AI MISUSE (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Completely confident (n = 84) 81% 19% Mostly confident (n = 130) 65% 35% Somewhat confident (n = 64) 60% 40% Not very/not at all confident (n = 39) 39% 61% Takeaway: When service-led suppliers are completely confident in their organization’s ability to minimize risks of AI misuse, 81% are optimistic about their company’s future; when confidence is low, only 39% are optimistic. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: INCREASES (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Revenue (n = 149) 79% 21% Spending on technology (n = 188) 67% 33% Number of FTE positions (n = 91) 78% 22% Work by suppliers vs. in-house (n = 63) 70% 30% Takeaway: Optimism about the company’s future is high when revenue (79%), technology spending (67%), staff size (78%), and/or outsourcing (70%) increase. Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: DECREASES (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Revenue (n = 84) 36% 64% Spending on technology (n = 21) 42% 58% Number of FTE positions (n = 69) 46% 54% Work by suppliers vs. in-house (n = 57) 42% 58% Takeaway: Lower levels of optimism about the company’s future are associated with decreasing revenue (36%), technology spending (42%), staff size (46%), and/or outsourcing (42%). Source: GRIT 2026 Insights Practice Report, Greenbook OPTIMISM ABOUT COMPANY: PERFORMANCE AGAINST GOALS (SERVICE-LED SUPPLIER) Optimistic Not Optimistic Exceeded (n = 105) 80% 20% Met (n = 117) 69% 31% Fell slightly short (n = 116) 43% 57% Takeaway: Service-led suppliers are most optimistic about their company when goals are exceeded (80%) than when goals are met (69%) and especially than when they fall short (43%). Source: GRIT 2026 Insights Practice Report, Greenbook THE BIG PICTURE [STRATEGIC INTERPRETATION] Mood tracks segment economics closely: the segments building capability — tech-led suppliers and those with 101–500 FTE — are the most confident, while the segments restructuring or under pressure are the least. Among the strongest performers, optimism about one’s own company is diverging from optimism about the industry; tech-led and 101–500 FTE suppliers are the most optimistic about themselves yet among the least confident in the industry’s future, which reads either as healthy self-reliance or as a warning that the industry’s most capable participants are decoupling from it. Service-led suppliers with 500+ FTE show the lowest company optimism, after a sharper single-year drop than anything during the pandemic. On the brand side, proximity to business decisions predicts confidence in one’s role: those in analytics, marketing, or executive positions, and those whose primary role is insights operations, are more optimistic than those in pure research provision. Two levers correlate with optimism throughout: clarity of AI expectations (more than whether guidelines are formal or informal) and the expectation that outsourcing will increase (84% optimism versus 58% on the brand side; 73% versus 46% among service-led suppliers). Most striking is a near-universal link between regular use of qualitative research providers — and, for brands, strategic consultants — and higher optimism, suggesting the industry still rewards the people-and-market expertise that automation cannot easily replace. Full analysis and supporting data: GRIT 2026 Insights Practice Report .