Metrics question
Imagine you are the PM in charge of Reactions on Facebook - the new way to interact with posts by using “love”, “haha”, “wow”, “sad”, and “angry” reactions. What would success look like in terms of number of non-like reactions per post at launch and how do you come up with this? Would this number differ by reaction? Why or why not?
- Meta
- Metrics
- Hard
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What this question tests
Tests defining launch success metrics for a new interaction pattern, and reasoning about why different reaction types would have different natural baselines.
How to approach it
- Clarify the feature: Reactions add five emotional response options beyond Like to posts.
- Define the launch success metric: non-Like reaction rate as % of total reactions on a post, since the goal is richer emotional signal, not just replacing Likes.
- Estimate a benchmark: reasonably assume Like remains dominant (people default to the familiar action), so assume 10-20% of total reactions being non-Like at launch is healthy, stated as an assumption.
- Explain why the number would differ by reaction: 'love' likely sees the highest adoption since it's a natural upgrade for already-Like-worthy content (baby photos, celebrations), while 'angry' or 'sad' are used on a narrower set of content (news, sensitive posts) so their absolute volume is naturally lower.
- Add a secondary metric: whether reaction diversity correlates with increased comments, since richer emotional signal should invite more nuanced discussion.
- Add a guardrail: monitor for misuse, e.g., 'haha' reacted to serious or tragic posts, which is a known real risk with this feature.
What a strong answer includes
- Gives a specific, reasoned answer to 'would this differ by reaction' rather than dodging the nuance in the question.
- Explains the distribution logic (love as a natural Like-upgrade, sad/angry tied to narrower content types) with real-world grounding.
- Proposes a guardrail for reaction misuse (e.g., 'haha' on tragic news), a genuine, well-known issue with this exact feature.
- States the launch benchmark explicitly as an assumption (10-20% non-Like share) rather than an unsupported hard number.
Common mistakes
- Answering only the first half of the question and ignoring 'would this differ by reaction, why or why not.'
- Treating all five reactions as interchangeable with no reasoning about content-type differences.
- No guardrail for reaction misuse on sensitive content, a real reputational risk for this feature.
Likely follow-up questions
- How would you detect and handle reaction misuse on sensitive posts?
- How would this metric evolve 6 months post-launch versus at launch?
- Would you weight reactions differently than Likes in News Feed ranking?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 2: Data fluency: SQL, logs, and reading the truth yourself
- Chapter 14: Get the job: the AI PM interview loop