Recollective is Making Global Research Truly Inclusive
One Recollective customer, an agency running healthcare and non-profit research, needed to engage researchers and policy influencers across developing countries on topics like mental health and infectious disease. Historically, they had to run separate studies in each language, hire local moderators, commission translations and then reconcile findings—a process that was slow, expensive and made cross-market interaction difficult.
Using Recollective’s AI-powered auto-translation capabilities, the team configured a single English study and then enabled translation into multiple languages with just a few clicks. Participants could contribute and interact in their own language, while the research team—working in English—could still follow, analyze, compare and respond with confidence based on the translation.
The client gained richer, more socially connected conversations across markets at a significantly lower cost and in a much quicker timespan. The confidence gained from that experience is leading them to explore other AI tools in Recollective such as AI interviews (Conversation Task) to enrich future work.
Turning Flat Responses Into Rich Dialogue
Another agency, working with a FMCG brand for an earplugs product, wanted to understand the buying mindset—from in-store behavior to packaging and messaging—but faced a familiar challenge. When participants are asked to imagine a future state or react to conceptual ideas in a standard open-text box, responses can be shallow and one-dimensional, limiting the value of the exercise.
In this case, the team combined asynchronous exploration, in-the-moment shop-alongs and a Conversational AI task as the final activity in a two-week study. Participants first reflected on the category and experience on their own, then moved into an AI-moderated Conversation Task where a responsive AI interviewer probed, asked follow-ups and helped them stretch and clarify their thinking. The result was a set of deeply nuanced, actionable insights—far beyond the one-line answers typical of traditional open ends—that could directly shape packaging, messaging and in-store strategy.
How to See the Whole Customer, Not Just a Single Study
A national Canadian retail brand recently acquired a heritage retailer and needed to quickly understand this newly acquired customer base ahead of the holiday season. The insights team ran two concurrent qualitative projects in separate study spaces—one blind, with general population consumers of the acquired brand, and one branded, with existing customers—but then faced the challenge of comparing large volumes of data across both audiences efficiently.
Using Multi-Project Ask AI in Recollective, the team could pose natural-language questions across both studies simultaneously, allowing them to explore similarities and differences between the audiences in a holistic way. This cross-project AI analysis enabled them to build a clear picture of the new consumer base, align it with their existing customers and support agile, well-informed decisions in time for a critical trading period—something the client said would have been very difficult without the efficiencies provided by AI.
AI That Enhances Human Insight
Across these examples, a common pattern emerges: AI is not replacing researchers, participants or stakeholders—it’s amplifying their contributions. Auto-translation expands who can be heard, conversational AI deepens how people are understood and multi-project analysis accelerates the path from raw data to strategic clarity.
When AI is designed to support human judgment rather than override it, market research teams gain the speed, inclusivity and depth they need to keep pace with a rapidly changing world.
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