Question 1

Does digital ethnography eliminate the need for traditional fieldwork?

Accepted Answer

Digital ethnography provides a convenient way to study consumers in their natural environment online, but it doesn't completely eliminate the need for traditional in-person fieldwork. Remote methods like online diaries, video interviews, and social media observation can capture rich insights at scale and across different regions without travel. However, there are still nuances that are best captured on the ground — things like the feel of a physical space, in-person body language, or unspoken cultural cues that a researcher can sense only by being there. Many organizations use a hybrid approach: leveraging digital ethnography for efficiency and breadth, and then doing selective in-person visits for depth on complex questions. This way, they get the scalability of digital methods without losing the contextual understanding that traditional fieldwork offers.

Question 2

How do we document model assumptions to meet governance and audit requirements?

Accepted Answer

Meeting model governance and audit requirements starts with thoroughly documenting all the assumptions behind your analytics or AI model. Create a formal model documentation file (sometimes called a model card or model memo) that lists the model's purpose, data sources used, and every key assumption made during development. This includes assumptions about the data (for example, assuming certain fields are accurate and representative), about the methodology (like assuming a linear relationship between two variables), and any parameters or thresholds chosen. Each assumption should be explained in plain language so that non-technical stakeholders and auditors can understand the logic. Also document the rationale or evidence supporting each assumption, and note any limitations that result. Keep this document version-controlled and updated whenever the model changes. By maintaining a clear, detailed record of assumptions, you make it easy for governance teams to review the model and for auditors to trace its compliance with policies.

Question 3

How should we set global templates without stifling local creativity?

Accepted Answer

Design global templates with a flexible framework: establish the core elements that must be consistent worldwide but leave room for local adaptation. For example, define standard metrics, questions, or brand elements that every market's version must include for consistency, while allowing regions to add custom sections, examples, or language nuances to fit their audience. In practice, many organizations use an 80/20 rule--around 80% of the template is standardized for global consistency, while 20% is open for local teams to tailor. Make it clear which parts of the template are mandatory and which are optional or modifiable, and even invite local teams to contribute ideas to the global template guidelines. This approach maintains a common structure for comparability but empowers local creativity, ensuring the template guides quality without becoming a one-size-fits-all straitjacket.

Question 4

Can AI tools improve alignment tracking across business units?

Accepted Answer

AI (Artificial Intelligence) tools can help organizations track alignment across business units by quickly analyzing communications and performance data for signs of divergence, but they work best as a supplement to human oversight. For instance, an AI system could scan project updates, team OKRs (Objectives and Key Results), or internal chat streams to highlight where one department's priorities or language deviate from the company's strategic objectives, using natural language processing to catch subtle differences. This kind of automated analysis can flag misalignments early - such as inconsistent customer messaging or duplicated efforts - allowing leaders to address issues before they grow. However, it's not a silver bullet: these systems may misinterpret context or nuance, so their findings should be interpreted by managers who understand the business environment.

Question 5

Can social listening sharpen stimuli before formal testing starts?

Accepted Answer

Yes, social listening can be used to refine and sharpen research stimuli (like concept descriptions, survey questions, or ad ideas) before formal testing begins. By analyzing what target consumers are organically saying online about the topic or category, you can identify themes, language and pain points that truly resonate. For example, if social media chatter reveals that people keep mentioning a specific frustration or using a particular slang term, you might incorporate those insights to make your concept more relatable or adjust your messaging. Social listening can also flag emerging issues or cultural nuances to avoid, helping you fine-tune stimuli so they align with current consumer sentiment. While social data isn't fully representative of everyone, it provides an early, unprompted feedback loop to optimize materials, leading to more relevant formal test results.

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