Metrics question
You're the PM of Facebook Birthdays. Birthday greetings drop one day; what do you do?
- Meta
- Metrics
- Medium
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What this question tests
Tests incident response and metrics thinking for a small but visible feature outage: triage, root cause, and how to measure whether it actually matters.
How to approach it
- Clarify severity: how many users were affected and for how long, since a single-day miss for a low-frequency feature needs a proportional response.
- Check root cause quickly: was it a backend outage, a timezone or data bug, or a dependency failure (push notification service).
- Assess user impact: birthday greetings are emotionally meaningful but low-frequency, so the priority is a fast, honest fix and communication, not a slow investigation.
- Ship a fix or workaround, such as manually triggering delayed greetings for affected users, then patch the root cause.
- Define a metric to confirm resolution and prevent recurrence, such as percentage of birthday notifications sent within the correct 24-hour window.
- Add a guardrail: alerting that fires if the daily notification volume deviates from the expected baseline.
What a strong answer includes
- Treats a small-seeming bug seriously because Birthdays is a trust and delight feature, not a core growth metric, so emotional impact outweighs raw scale.
- Prioritizes a fast fix and clear user communication (a make-good, like a later greeting) over a lengthy root cause investigation first.
- Proposes a concrete monitoring metric (percent sent within window) to catch this class of failure before users notice next time.
- Distinguishes between the immediate incident response and the longer-term guardrail to prevent recurrence.
Common mistakes
- Dismissing the bug as low priority just because Birthdays is not a core growth feature.
- Jumping straight to a fix without proposing a monitoring guardrail to catch it earlier next time.
Likely follow-up questions
- How would you decide whether this needs a user-facing apology or explanation?
- What monitoring would have caught this before any user noticed?
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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