8 Ways Market Researchers Are Using AI-Moderated Interviews (AIMIs)

Across the industry, market researchers are rethinking how they gather data. The transformative shift from static, closed-ended surveys to hybrid studies powered by AI-moderated interviews is ushering in a new era of market research. 

Instead of choosing between quantitative scale and qualitative depth, researchers can now capture both - thousands of structured answers and thousands of authentic voices - in a single process. 

AI-moderated interviews (AIMIs), available through end-to-end platforms like Glaut, address the need for large sample sizes, speed, and the ability to understand the reasons behind each percentage. The AI-moderator leads a voice-based conversation, probes naturally, recognizes emotions, and understands in real time whether the respondent is engaged. Then, the platform collects verbatim and audio data and analyzes it using different layers of analysis: thematic analysis, sentiment analysis, emotion analysis, and interpretative analysis. 

The outcome: quicker learning cycles, deeper understanding, more profound empathy, and decisions based on genuine human reasoning. Here are eight ways researchers are already using AI-Moderated Interviews to address long-standing challenges in their work. 

1. Market exploration: testing new verticals with agility 

A leading mental health company aimed to understand how people perceive digital wellness services before expanding into new product lines. Using Glaut’s AI-moderated interviews, the research team explored perceptions, barriers, and motivations among potential users, collecting over a thousand interviews in a single day. The asynchronous format gave participants space to express nuanced emotions, from curiosity to skepticism, revealing what makes digital health credible or distant in people’s minds. By combining open conversations with structured closed questions, the team validated its go-to-market strategy in record time. 

The results: 

• 1012 interviews completed 

• 1 day from brief to insights 

• 71% of key insights emerged during conversational follow-ups 

• 3.5× cheaper than a quant + qual focus group 

2. Customer experience trackers: adding emotional depth to longitudinal studies 

Customer-experience programs often depend on metrics like NPS, but numbers alone can’t explain why satisfaction increases or decreases. Breakthrough Research added Glaut to its automotive tracker to capture the human stories behind the scores. AI moderation turned standard surveys into dynamic conversations, uncovering the expectations, frustrations, and emotional moments that influence brand loyalty. 

The results: 

• 251 interviews completed 

• 9 days from brief to insights 

• 1.72 themes per response on average 

• 3× cheaper than combined quant + qual studies 

“Richer open-ends to elevate our online surveys and complement our in-house AI-powered innovation tools,” said the agency’s VP of Research. VP of Research. 

3. Customer journey in retail: mapping motivations at scale 

Understanding why shoppers buy is as important as knowing what they buy. A retail insights team studying online fashion behavior replaced lengthy focus groups with AI-moderated interviews. 

Participants were asked to recount their most recent purchase experience, from discovery to checkout, while the AI explored their expectations, touchpoints, and emotions. Over just 4 days, the team collected 1,000 complete purchase stories and identified three common themes in each response. This method revealed previously overlooked friction points, like sizing confidence and post-purchase reassurance, and it achieved this twice as cost-effectively as a traditional mixed-method approach. 

The results: 

• 3 themes mentioned per answer on average by respondents 

• 2× cheaper than a mixed quant + qual study 

4. Brand awareness: listening to emerging audiences 

Reaching younger consumers is one of the toughest challenges in research. Mondadori Media, part of the leading European media group, used AI-moderated interviews to listen directly to children and teenagers about the brands they love. Over 1,600 kids aged 3-13 recorded short, playful voice responses describing their favorite gifts and the brands associated with them. The AI moderator engaged with natural, age-appropriate questions, eliciting authentic emotional responses instead of rehearsed replies. More than half of all insights originated from these spontaneous follow-ups, aiding the company in recognizing which brands were resonating with new generations. 

The results: 

• 1.600 interviews completed across kids aged 3-13 years old 

• 8 days from brief to insights 

• 54% of insights emerged during follow-ups 

• 5× cheaper than traditional methods 

• 24 brands mentioned spontaneously 

“With Glaut, we gained direct insights from kids and teens about their Christmas gift wishlists, and the brands they want them from. This allowed us to shape partnership and co-branding strategies better.”, said Pamela S., Head of Research, Mondadori Media. 

5. Concept & product testing: turning feedback into direction 

Early-stage concept testing often requires a balance of quantitative data and nuanced insights. A European research institute utilized Glaut’s AIMIs to assess a new sports equipment prototype by combining structured ratings with open, voice-based feedback. Participants responded naturally to images and descriptions, while the AI interpreted terms like “innovative,” “useful,” or “too expensive,” clarifying their meaning within the context. 

The results: 

• 1,012 interviews completed 

• 9 days from brief to insights 

• 1.91 themes per answer on average 

• 4.5× cheaper than quant + qual IDIs 

• 6-minute average interview length 

6. Pre-screening for qualitative studies: selecting high-value participants faster 

Recruiting participants for qualitative studies is often slow and uncertain. A U.S. research company improved this by implementing AI-moderated interviews as an initial screening. Instead of traditional forms or brief calls, respondents recorded voice responses that showcased their personality, engagement, and communication style. Researchers then reviewed 70 hours of recordings and chose the 30 most articulate and reflective individuals. This new process shortened recruitment from weeks to just two days and lowered costs by a factor of five. 

The results: 

• 371 interviews completed 

• 2 days from brief to insights 

• 70 hours of qualitative data analyzed 

• 5× cheaper than traditional recruiting 

• 30 high-quality participants selected 

7. Doctors’ experience (B2B): engaging hard-to-reach professionals 

Healthcare research frequently faces low response rates. A research agency addressing doctors’ educational needs switched from phone interviews to AI-moderated voice chats. Physicians responded at their convenience during breaks or commutes, which increased engagement and yielded more thoughtful answers. Personalized AI follow-ups asked for reasoning and examples, generating three times more detailed data than previous CATI methods, saving both time and budget. 

The results: 

• 301 interviews completed 

• 9 days from brief to insights 

• 3× richer answers than prior methods 

• 4× cheaper than CATI 

“We collected about 3x richer answers (more evidence collected) with Glaut compared to other research methodologies used before. Glaut personalized follow up increased also the Quality of responses, when compared to the previous research method whose follow-ups were generic.”, said Kyle H., Head of Quantitative Research, ELMA Research UK 

8. Political opinions: capturing public sentiment through voice 

Traditional polling measures numbers, while AIMIs capture narratives. A research team studying voter attitudes before a national election used Glaut to gather spontaneous insights on leadership, trust, and future outlooks. Participants spoke openly, often discussing topics beyond typical survey questions. This project demonstrated how voice-based AI can enhance social and political research by transforming raw data into stories about what citizens truly care about. 

The results: 

• 504 interviews completed 

• 3 days from brief to insights 

• 2.06 themes per answer on average 

• 4× cheaper than CATI polling 

• 14-minute average interview length 

Conclusion 

AI-moderated interviews are transforming research in a way similar to how online surveys did 25 years ago: they are redefining how insights are gathered and analyzed. They don’t replace researchers but enhance their capabilities. Tools like Glaut free experts from repetitive tasks, enabling them to research 50+ languages simultaneously and focus on applying insights to better business decisions. 

AI tools provide the missing depth that surveys only offer efficiency and percentages, converting each answer into context and every conversation into actionable data. AIMIs combine speed, scale, and depth, making research faster, more adaptable, and more connected to real people. 

Through Glaut Research, our research-on-research initiative, we test and validate AIMIs alongside traditional methods to build an evidence base for this new approach. In collaboration with independent researchers, market research firms, and academic institutions, we are shaping the next standard for generating insights, and expanding understanding.