Metrics question
You are the PM of Instagram app. The MAU has been constant but DAU has declined. What will you do?
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
Tests diagnosing a specific engagement divergence (stable MAU, falling DAU), which signals a frequency/habit problem, not an acquisition problem.
How to approach it
- Interpret the divergence: reach is fine (MAU stable) but existing users open the app less often (DAU falling).
- Compute stickiness (DAU/MAU) by cohort: new users, users active 3-12 months, and long-tenured users, to find where it's dropping.
- Check product causes: a feed algorithm change, competitor apps pulling time away, or a bug slowing load times.
- Check content supply: are the accounts a user follows posting less, reducing their reason to open daily.
- Check competitive timing: does the decline line up with a rival's feature launch, e.g., a short-video competitor gaining share.
- Prioritize the steepest-declining cohort for a deep dive, then A/B test a fix like re-engagement notifications before a broad rollout.
What a strong answer includes
- Correctly reads what stable MAU plus falling DAU implies (a frequency problem, not acquisition), showing precise metric literacy.
- Segments by cohort to localize the drop instead of treating it as uniform across all users.
- Names a content-supply hypothesis (people they follow posting less), often overlooked versus purely internal causes.
- Proposes segment-specific next steps rather than one blanket fix.
Common mistakes
- Treating this as generic 'engagement is down' without reading what the specific pattern implies.
- Jumping to a fix before diagnosing where and why frequency dropped.
- Ignoring competitive and content-supply causes in favor of only internal bugs.
Likely follow-up questions
- How would you distinguish a competitive cause from an internal one quickly?
- Which cohort would you investigate first?
- How would you test re-engagement notifications without causing opt-outs?
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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