Product design question
Pick a music/podcast app. Why do you like it? On the flip side, what do you not like about it? What improvements would you suggest?
- DoorDash
- 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 improvement and self-awareness: giving specific, structured product criticism with a clear proposed fix.
How to approach it
- Pick a specific app, such as Spotify, to keep the answer concrete and credible.
- State what you like: a specific strength, like personalized playlists such as Discover Weekly.
- State what you dislike: a specific weakness, like inconsistent podcast discovery or cluttered navigation.
- Propose one focused improvement tied to the weakness, such as a dedicated podcast tab with better recommendations.
- Define how you would measure whether the improvement worked, like increased podcast listening time.
What a strong answer includes
- Names a real, specific feature for both likes and dislikes rather than vague praise or complaints.
- Proposes a focused, buildable fix instead of a wish list of unrelated features.
- Ties the fix to a plausible metric, e.g. 10 percent increase in podcast session length.
- Shows product judgment by explaining why this fix matters more than other possible changes.
Common mistakes
- Giving vague opinions like 'I just don't like the design' with no specifics.
- Proposing an improvement unrelated to the stated dislike.
- Not offering any way to measure success of the proposed change.
Likely follow-up questions
- How would you prioritize this fix against other roadmap items?
- What data would you want to see before building this?
- Why do you think the current team hasn't already fixed this?
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- Which app have you used for finding an apartment? How would you improve it?DoorDash · Product design · Easy
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More questions from DoorDash
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