Turning Customer Interviews Into Insight
Go from a pile of interview transcripts to findings you can defend, with every quote traceable
A taste of a lesson
The AI said 'most users find onboarding confusing'. Can I put that in my findings deck?
Not yet. 'Most users' is a prevalence claim, and interviews can't support it, so first find out what's underneath. Ask the assistant for every verbatim quote about onboarding with participant code and timestamp, then check each one in the transcript. If four of your nine participants describe getting stuck at the same step, write exactly that: 'Four of nine participants got stuck connecting their bank account', with two quotes. That's specific and true. Try it now: how many distinct participants does your onboarding theme actually have?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Plan interview questions that capture past behaviour rather than wishful predictions
- Prepare transcripts safely by removing identifying details before using AI tools
- Use an AI assistant to tag and cluster quotes with participant IDs and locations
- Verify AI generated themes and quotes against the original transcripts
- Write a short findings page that separates evidence, interpretation and next tests
Lesson plan
- 1 Start from the decision Define the decision your research informs and the questions that would change it. Start
- 2 Interviews that produce usable evidence Run interviews that capture specific stories instead of opinions and polite praise. Start
- 3 Preparing transcripts safely Get transcripts into a clean, consistent, de identified format ready for analysis. Start
- 4 AI assisted tagging and clustering Use an assistant for a first pass that produces traceable quotes, not loose summaries. Start
- 5 Checking the synthesis Catch invented quotes, overweighted voices and missing disagreement before anyone sees the findings. Start
- 6 Writing findings people can challenge Produce a one page findings document with evidence, caveats and the next test. Start
Try asking
About this tutor
For product managers, founders, designers and marketers who run customer interviews and then struggle to turn them into decisions. You will learn to plan interviews that produce usable evidence, prepare transcripts safely, use an AI assistant to tag and cluster what people said, and check every claim against the source. The lessons work on your own interview notes or on a practice set the tutor provides. By the end you will have a repeatable synthesis method that separates what customers did from what they said they might do, and a short findings document your team can challenge and trust.
Reviews
4.7
3 ratingsSample
- Chiamaka O.Sample
Good on the boring but important parts: consent, removing names, keeping line numbers. My findings page is shorter now and my team argues with the evidence, not with me.
- Henrik A.Sample
Counting participants instead of mentions changed how I read my own research. One customer had been driving half my themes. Would have liked more on recruiting interviewees.
- Marisol V.Sample
The 'not found instead of guessing' instruction alone saved me. Two quotes the AI gave me did not exist in the transcripts. Now I check everything against timestamps before it goes in a deck.
About the teacher
Product management for AI features: deciding, specifying, testing and pricing them well
9 tutors 388 lessons taught Sample
I teach product managers and founders how to build AI features that people trust and keep using. I come from product work on software teams, where I learned that the hard part of an AI feature is rarely the model. It is deciding whether the feature should exist, writing down what good looks like, testing it before customers do and...
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