Product design question
Design a Facebook feature that measures user happiness.
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
Metrics design skill applied to a fuzzy human construct, checking whether you can operationalize 'happiness' into measurable, ethical proxies.
How to approach it
- Clarify what happiness means here: momentary positive sentiment while using the app, or broader wellbeing from using it, since Meta has been criticized for ignoring the latter.
- Reject self-report-only measures as the sole signal, since surveys have low response rates and recall bias, but keep them as a periodic validation check.
- Propose behavioral proxies: ratio of positive reactions to negative ones on content a user posts or comments on, time spent on content associated with self-reported high mood in past surveys, and reduced doom-scrolling patterns like long passive sessions with low interaction.
- Combine proxies into a wellbeing index rather than a single metric, since any one signal alone can be gamed or misleading.
- Address the ethical risk directly: this data must not be used to manipulate engagement, only to inform product changes that genuinely improve wellbeing.
- Define success as improvement in the wellbeing index correlated with periodic survey validation, not raw engagement.
What a strong answer includes
- Builds a composite index instead of one fragile proxy metric, showing awareness that happiness cannot be reduced to a single number.
- Explicitly separates measurement from misuse, naming the ethical risk of using happiness data to increase addictive engagement instead.
- Anchors behavioral proxies to periodic survey validation, catching cases where behavior and self-reported mood diverge.
Common mistakes
- Proposing time spent as the sole happiness metric, which actually measures engagement, not wellbeing, and can be directly contradictory.
- Ignoring the ethical risk that this feature could be misused to optimize for addictive rather than healthy engagement.
Likely follow-up questions
- How would you prevent this metric from being used to justify more addictive design?
- How would you validate that your proxies actually correlate with real happiness?
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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