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At IIEX.AI 2024, I presented the AIMI (Artificial Intelligence Moderated Interviews), an innovative research methodology created by Glaut that redefines qualitative research, bridging in-depth insights with scalable efficiency. AIMIs are human structured, AI-moderated, voice-answered interviews, available in +50 languages. Designed to conduct real-time, AI-moderated interviews across multiple languages, AIMI allows researchers to gather nuanced feedback at scale.

What makes AIMI so unique?

AIMIs allow qualitative research to achieve the scale of traditional quantitative studies without sacrificing insights. Through a voice-based AI-interviewer, it engages respondents in natural conversation, collecting rich, open-ended responses. Researchers can structure questions to fit specific project needs, while AIMI’s AI seamlessly moderates and follows up, probing into key themes. The results are processed quickly, using Glaut’s 3-steps framework  (Define, Measure, and Interpret -DMI) to convert these responses into structured, actionable insights.

The DMI Framework

‍Glaut’s DMI process offers a clear path for analyzing huge volume of unstructured data, like thousands of interviews:

1. Define the taxonomy of topics and sub-topics ex-post, based on participant responses (and not based on pre-defined hypothesis).
2. Measure the sentiment of each response, to assess the tone and direction of each response.
3. Interpret the data, through a combination of narrative, quantitative data and verbatim extracted from the interviews.

With this method, AIMI produces insights that genuinely reflect participants’ views without predefined limitations. This flexible taxonomy allows for emergent insights, capturing what matters most to respondents.

Real-world application: The U.S. election tracker

Glaut leveraged AIMI’s potential in the first Qualitative Tracker created for the U.S. election, in collaboration with Altum Insight, a leading political research firm. Conducting in-depth interviews with 1,500 participants across swing states, Glaut captured voter sentiment on candidates’ policies and personal qualities replacing old-style surveys with dozens of questions and Likert-scale answers, with just two open-ended questions:

“What do you think about candidate A?” and “What do you think about candidate B?”

Once +1,500 AIMIs were collected (over 200 hours of qualitative research!), Glaut software organized the responses into hundreds of sub-topic (or “codes), and then grouped them into 10 major topics (or “themes”). This is the opposite of a standard suvey approach, in which the taxonomy is defined ex-ante and often biased. Using AIMIs, Glaut created the taxonomy ex-post, revealing insightful trends around what people really think about US presidential candidates, their perceived empathy, communication, and leadership style, among others. This innovative approach allowed for detailed insights that would have been impossible to achieve  with traditional survey methods and extremely expensive with human led interviews..

Why AIMI are redefining market research‍

We believe that AIMIs are improving research for both sides of the table. For researchers, AIMIs allow for qualitative research at scale. For respondents, AIMIs allow for faster responses, a more engaging experience, which leads to reduced fatigue and higher completion rate. Voice-based responses allow respondents to express themselves freely, and open-ended questions encourage honest, in-depth answers. By adapting in real-time, AIMI provides timely insights, empowering researchers to make data-driven decisions quickly and affordably.

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Conclusion

AIMI represents a step forward in market research, combining the depth of qualitative analysis with the efficiency of AI. By making large-scale, insightful interviews possible, Glaut’s AIMI is paving the way for a new standard in research methodology. To see AIMI in action on the US Presidential election Tracker, check out the full IIEX.AI presentation below and discover how it could elevate your research strategy.

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