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Metrics & AnalyticsFoundationalFree
Choose the Success Metric for a Feature
Tests whether you can connect a feature to genuine value - and resist vanity metrics.
Interview prompt
You just launched [a feature, e.g. Stories]. How do you measure its success?
What interviewers evaluate
- Do you tie the metric to the feature's goal and the company mission?
- Do you pick ONE primary metric, not a dashboard of vanity metrics?
- Do you include guardrail metrics to catch unintended harm?
- Do you reason about leading vs lagging indicators?
- Do you consider cannibalization and second-order effects?
A framework to structure your answer
- Goal - why does this feature exist? What user/business outcome is it meant to drive?
- Primary metric - choose one metric that best captures that outcome (an action tied to value, not a raw count).
- Guardrails - name metrics that must NOT degrade (e.g. overall engagement, revenue, latency, the cannibalized surface).
- Leading vs lagging - identify a leading indicator you can read quickly and the lagging outcome it should drive.
- Cannibalization - check whether the feature just shifts behavior from elsewhere rather than adding value.
Strong sample answer
Try structuring your own answer first, then reveal a strong worked example.
Common variants
- What's the north-star metric for [WhatsApp / YouTube / LinkedIn]?
- How would you measure the health of a marketplace?
- Pick one metric to optimize the whole company around - which and why?
Pitfalls to avoid
- Choosing a vanity metric (raw clicks, page views) instead of one tied to value.
- Listing 10 metrics with no single primary.
- Forgetting guardrails - so a 'win' could be hiding harm.
- Ignoring cannibalization (the feature just moved engagement around).
- Picking a metric you can't actually measure or attribute.
Likely follow-ups
- Stories usage is high but overall time-spent is flat. Success or failure?
- How would you set up an experiment to attribute the lift?
- What guardrail would make you roll it back?