Product design question
Design an application that helps students with their mental well-being.
- Meta
- Product design
- Easy
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What this question tests
Product design for a sensitive wellbeing category, requiring privacy-aware, non-clinical design appropriate for students.
How to approach it
- Segment users: students facing everyday stress versus students needing more serious mental health support, since the product should route appropriately.
- Identify the pain point: students often don't seek help early because of stigma, cost, or not knowing where to start.
- Prioritize the everyday-stress segment as the primary experience, with clear pathways to professional resources for more serious needs.
- Design the solution: low-friction daily mood check-ins, anonymous moderated peer support spaces, and coping resources tied to common triggers like exams.
- Add a safety layer: clear escalation paths to campus counseling or crisis resources when check-ins indicate serious concern.
- Define success: consistency of check-in use and self-reported stress trend, alongside successful referrals to professional support.
What a strong answer includes
- Explicitly separates everyday stress support from serious mental health needs, avoiding the trap of positioning the app as a clinical replacement.
- Names stigma and cost as the real adoption barriers this product should address.
- Proposes a concrete escalation mechanism to professional help, a critical safety design element.
- Uses check-in consistency and successful referrals as success metrics, balancing engagement with genuine safety outcomes.
Common mistakes
- Positioning the app as a substitute for professional mental health care without a clear escalation path.
- Ignoring stigma and privacy as core adoption barriers for a sensitive topic.
- Treating all student mental health needs as the same severity.
Likely follow-up questions
- How would you handle a user showing signs of a serious crisis through the app?
- How would you build trust around privacy for such sensitive data?
- How would you measure success without over-relying on self-reported data?
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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