Metrics question
What metrics would you use to measure notifications at Facebook?
- Meta
- Metrics
- Medium
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What this question tests
Tests defining a balanced metric set for a feature whose overuse directly harms the user experience, requiring engagement and annoyance to both be measured.
How to approach it
- Clarify the goal: notifications exist to re-engage users with relevant activity, but excessive or irrelevant notifications drive annoyance and opt-outs.
- Define primary metrics: click-through rate per notification type, a comment, a tag, a friend request, and session opens attributable to a notification.
- Define a quality metric: relevance rate, the share of notifications clicked versus dismissed or ignored, segmented by type.
- Define a guardrail: notification opt-out or mute rate and app-level permission revocation rate, since these directly signal notification fatigue.
- Define a downstream metric: whether a click leads to a further action, reply or like, versus just opening and immediately leaving.
- Prioritize the guardrail, opt-out rate, as a hard ceiling: any push to increase notification volume must not increase this metric.
What a strong answer includes
- Explicitly pairs an engagement metric, click-through, with an annoyance guardrail, opt-out rate, reflecting the double-edged nature of notifications.
- Segments click-through by notification type, recognizing a friend request and a group post have very different natural baselines.
- Proposes a downstream action metric, distinguishing a genuinely valuable notification from a bare click-and-leave.
- Sets the guardrail as a hard ceiling on volume decisions, showing sound product judgment about the risk of overuse.
Common mistakes
- Measuring only click-through rate or volume sent, ignoring the real risk of notification fatigue and opt-outs.
- Treating all notification types as equivalent, missing that baselines vary hugely by type.
Likely follow-up questions
- How would you decide which notification types to reduce if opt-out rate started climbing?
- How would you personalize notification frequency per user?
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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