Strategy question
You are the PM at Facebook Post. What reactions should we add next?
- Meta
- Strategy
- Medium
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What this question tests
Product thinking on expanding a lightweight interaction feature without diluting its simplicity or signal value.
How to approach it
- Clarify the goal: are new reactions meant to increase expression richness, engagement, or better sentiment signal for ranking.
- Assess current gaps: existing reactions like Like, Love, Haha, Wow, Sad, Angry may miss nuanced sentiments like support or curiosity.
- Prioritize by evidence: look at comment text analysis for sentiments not captured by existing reactions, like empathy for difficult posts.
- Propose a specific addition, for example a Support or Care-style reaction for posts about hardship, filling a real emotional gap.
- Weigh the tradeoff: too many reaction options increases decision friction and dilutes the simplicity that makes reactions fast to use.
- Success metric: adoption rate of the new reaction, and whether it reduces low-signal comment volume on relevant post types.
What a strong answer includes
- Identifies a real, specific gap, like the lack of empathetic non-celebratory reactions, grounded in Facebook's actual known reaction set (common knowledge).
- Weighs the tradeoff explicitly: more reactions add expressiveness but risk diluting the one-tap simplicity that makes reactions valuable.
- Ties the new reaction to a measurable signal improvement, not just novelty.
Common mistakes
- Proposing many new reactions at once without weighing added complexity.
- No evidence or reasoning for why the specific new reaction fills a real gap.
- Ignoring that reactions also feed content ranking, not just user expression.
Likely follow-up questions
- How would you decide which reaction to remove if you added a new one?
- How would this new reaction affect content ranking signals?
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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 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop