AI Interview Questions for Customer Research

The discussion guide is the foundation of every AI interview study. But designing questions for AI moderation requires a different approach than designing survey questions or even traditional IDI guides. The AI moderator will generate its own follow-up probes — your job is to provide opening questions that create the right conditions for deep exploration.

These 50 questions are organized by research context and designed to give AI-moderated interviews the launching points they need for 5-7 level laddering depth.

Principles for AI Interview Questions

Open-ended, not leading. “Tell me about your experience with…” not “Did you find the onboarding confusing?”

Behavioral, not hypothetical. “Walk me through the last time you…” not “Would you ever consider…”

Specific, not abstract. “Think about the moment you decided to cancel…” not “How do you feel about our product?”

Permission-giving. “There are no wrong answers — I’m genuinely curious about your experience” signals to participants that honesty is valued.

Churn Research Questions (10)

1. Walk me through the journey from when you first started considering leaving to when you actually made the decision.
2. Think back to the specific moment when canceling shifted from a possibility to a probability. What was happening?
3. Before you decided to leave, what did you try to make it work? What happened with those attempts?
4. If you could change one thing about your experience that would have prevented you from leaving, what would it be and why?
5. How did you explain your decision to leave to your team or colleagues?
6. What were you hoping would be different about the alternative you chose?
7. Looking back, was there a point where you felt like the relationship was still salvageable? What would have needed to happen?
8. How has your day-to-day changed since switching? What’s better and what do you miss?
9. If someone on your team suggested going back, how would you respond and why?
10. What would we need to demonstrate for you to consider returning?

Win-Loss Research Questions (10)

11. Take me back to the beginning — what triggered the search for a solution in the first place?
12. Who else was involved in the decision, and what did each person care about most?
13. Walk me through how you narrowed your options from many to the final two or three.
14. What was the single most important factor in your final decision, and why did it matter so much?
15. Was there a moment during the evaluation where your preference shifted? What caused it?
16. How did you justify your choice to the person who had to approve the budget?
17. What concerned you most about the option you chose? What made you decide to proceed despite that concern?
18. Looking back three months later, how does the reality compare to what you expected during the evaluation?
19. If you had to make the same decision again today, would you choose differently? Why or why not?
20. What’s one thing the vendor you didn’t choose could have done to change the outcome?

Concept Testing Questions (10)

21. When you first saw this concept, what was your immediate gut reaction — before you started thinking about it analytically?
22. Who in your life or organization would this be most useful for, and why them specifically?
23. What would need to be true about your situation for you to actually purchase this?
24. What’s the first question or concern that comes to mind when you consider adopting this?
25. How would you describe this to a colleague who hasn’t seen it?
26. What does this remind you of — either positively or negatively — from your past experience?
27. If this cost twice as much, would you still consider it? What if it cost half as much — would that change your perception?
28. What’s missing from this concept that would make it a clear yes for you?
29. How would adopting this make you feel professionally? What would it say about your judgment?
30. If you saw a competitor using this, would that make you more or less interested? Why?

UX Research Questions (10)

31. Walk me through what you were trying to accomplish and what happened step by step.
32. Was there a moment where you felt confused, stuck, or uncertain about what to do next? Describe that moment.
33. What did you expect to happen when you clicked/tapped that? What actually happened?
34. If you were explaining this experience to a friend, what words would you use?
35. How does this experience compare to similar tools or products you’ve used?
36. What workaround did you develop to get past the friction point, and how does that workaround feel?
37. If you could redesign this one interaction, what would you change and why?
38. How did this experience affect your confidence in the overall product?
39. Would you recommend this product to someone with your level of technical skill? Why or why not?
40. What’s the one thing that would make this experience go from acceptable to genuinely enjoyable?

Brand Perception Questions (10)

41. When you hear our brand name, what’s the first thing that comes to mind — an image, a feeling, a memory?
42. If our brand were a person, how would you describe their personality?
43. Think about the last time you recommended (or didn’t recommend) us to someone. What drove that decision?
44. What would you lose if our brand disappeared tomorrow? What would you gain?
45. How does using our brand make you feel about yourself — professionally or personally?
46. Who do you think our brand is really made for? Do you see yourself as that person?
47. If you were introducing our brand to a skeptic, what would you say to convince them?
48. What’s the biggest gap between what our brand promises and what it actually delivers?
49. How has your perception of our brand changed over the past year, and what caused that change?
50. If our brand made one change that would make you genuinely proud to be associated with it, what would that change be?

Using These Questions with AI Moderation

These questions are starting points — the first rung of the ladder. The AI moderator will take each response and probe deeper: asking why that matters, what’s behind that feeling, when that concern first emerged, and what it means for the participant’s identity and values. The quality of that probing depends on how the AI adapts across multiple dimensions — not just generating follow-ups, but calibrating depth, tone, and direction to each participant’s responses.

For a complete guide to designing AI interview studies, see AI Customer Interviews: The Complete Guide. To see how these questions translate into 30+ minute conversations with 5-7 level depth, book a demo.