Question 1

How are location triggers changing in-the-moment capture?

Accepted Answer

Location-based triggers (like geofences or beacons) are transforming in-the-moment research by prompting participants at the right place and time. Instead of relying on someone to recall an experience later, researchers can set a trigger so that when a participant enters or leaves a specific location, they get an automatic prompt on their smartphone to give immediate feedback. For example, a short survey can pop up right after a person exits a store or visits a particular venue. By capturing reactions in real time, the data is richer and more accurate - people describe their impressions while the memory is fresh, rather than hours or days afterward. Location triggers also enable context-aware questions (asking about a display or promotion at the moment a shopper actually sees it). Overall, smart location prompts are turning in-the-moment capture from a manual, hit-or-miss effort into a more automatic and precise process.

Question 2

How can loyalty research capture younger consumers' shifting brand expectations?

Accepted Answer

Loyalty research can capture younger consumers' shifting brand expectations by focusing on the new factors that drive their loyalty, such as authenticity, shared values, and unique experiences. Traditional surveys about points and discounts might miss what matters to Gen Z and younger millennials, so studies should also ask how things like a brand's social responsibility, personalization, or community involvement affect their willingness to stay loyal. For example, you might measure emotional connection or the importance of a brand aligning with their values, not just satisfaction scores. Methods like qualitative interviews or social media listening can uncover emerging expectations--like the desire for more two-way engagement or instant rewards--that would help loyalty programs evolve. By broadening loyalty research beyond old-school rewards metrics, you capture what really makes younger consumers stick with or switch away from a brand.

Question 3

How do we increase stakeholder engagement with trackers?

Accepted Answer

The best way to increase stakeholder engagement with trackers is to ensure the tracking study delivers accessible, relevant insights tailored to their needs. Present data through interactive dashboards or concise, story-driven reports that highlight key trends and their business implications, ensuring busy stakeholders see immediate value. For example, you might set up automated alerts or AI-driven highlights when important metrics shift, drawing attention to changes that require action. Also involve stakeholders early — let them help define which KPIs the tracker monitors or invite them to periodic review sessions — so they feel ownership of the process. Ultimately, engagement rises when the tracker isn't just numbers on a slide but a decision-making tool that directly supports their goals in their day-to-day work effectively.

Question 4

Can AI unify cross-channel data without over-attributing impact?

Accepted Answer

Yes, AI can unify cross-channel marketing data into a holistic view that fairly attributes impact, but it needs careful design to avoid over-crediting any one channel. Advanced AI-driven attribution models (for example, using machine learning or Shapley value-based algorithms) can ingest data from all touchpoints — social, email, search, offline — and assign proportional credit to each. The key is training the model on accurate conversion data and setting constraints or validation checks so it doesn't blindly favor the last click or the most frequent channel. When implemented correctly, the AI recognizes how channels work together (say, a social ad that assists a later search click) and distributes credit accordingly. Properly calibrated, an AI attribution system avoids the common pitfall of giving too much weight to easily trackable channels and instead provides a balanced read on what drives conversions.

Question 5

Does longer time spent in-store always signal greater engagement?

Accepted Answer

Not necessarily — spending more time in-store doesn't automatically equate to greater engagement. Extra time can be positive (browsing multiple aisles, trying demos, asking questions) or negative (searching for a product due to poor signage, waiting in a long checkout line). For example, a shopper lingering by choice to compare options is likely engaged, but one stuck waiting for assistance is experiencing frustration, not delight. Context and companion metrics matter: if longer visits coincide with higher conversion rates or interaction with displays, that suggests genuine engagement. But if baskets stay empty or complaints rise with longer store time, the time is reflecting friction. In short, more time in a store is only a good sign when it's spent meaningfully — otherwise it may signal issues rather than enthusiasm.

dichter & neira Latin America & the Caribbean

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Services and Expertise

Market Research FAQs with Expert Insights

How are location triggers changing in-the-moment capture?

How can loyalty research capture younger consumers' shifting brand expectations?

How do we increase stakeholder engagement with trackers?

Can AI unify cross-channel data without over-attributing impact?

Does longer time spent in-store always signal greater engagement?