Product design question
Design a tool to collect customer feedback on an app (any app).
- Microsoft
- Product design
- Easy
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
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What this question tests
Product sense on a horizontal, generic tool: forcing specificity by picking a concrete context despite the vague prompt.
How to approach it
- State the ambiguity upfront and pick a concrete example app to design for, such as a food delivery app.
- Identify who gives feedback: power users, one-time users, and churned users, and note their different motivations.
- List collection moments: in-app prompts after key actions, a persistent feedback button, and post-churn surveys.
- Design the core flow: a lightweight 1-tap rating plus optional open text, triggered right after a relevant action.
- Define how feedback routes to the team and a metric, like response rate or percent of feedback actioned.
What a strong answer includes
- Picks a specific app and moment (e.g. right after a completed order) instead of a generic feedback form.
- Separates quick signals (thumbs up or down) from deeper qualitative input to reduce friction.
- Proposes routing negative feedback to a priority queue so it gets acted on, not just archived.
- Uses an assumed target, e.g. 15 percent response rate, to anchor the discussion.
Common mistakes
- Designing a generic survey with no trigger logic or timing.
- Never closing the loop on what happens to the feedback after collection.
- Ignoring survey fatigue from asking too often.
Likely follow-up questions
- How would you avoid annoying users with too many prompts?
- How would you prioritize which feedback to act on first?
- How would you measure whether the feedback tool is working?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 7: AI UX and human oversight: design for a system that is wrong sometimes
- Chapter 14: Get the job: the AI PM interview loop