Metrics question
You are a PM at YouTube. You released a new feature. It doesn't matter what feature was released. After the release, number of mobile video views went up by 10%, and number of desktop comments under videos went down by 20%. What would you do?
- Meta
- Metrics
- Hard
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What this question tests
Diagnosing a metric divergence after a launch: separating a real causal link from coincidence across platforms.
How to approach it
- Confirm both numbers are measured correctly and over the same time window, ruling out a tracking issue first.
- Check whether the feature itself touched desktop comments at all, or if this is a coincidental, unrelated shift.
- Segment desktop comments by user type and content category to see if the drop is broad or concentrated.
- Check whether mobile growth is cannibalizing desktop usage, for example users shifting from desktop to mobile entirely, not just commenting less.
- Decide whether the trade off is net positive, based on which metric matters more to the north star, and propose next steps.
What a strong answer includes
- Considers cannibalization directly, hypothesizing that users moved from desktop to mobile rather than commenting less overall.
- Segments the desktop drop by user cohort to check if it is broad or isolated to specific users.
- Weighs the trade off explicitly, for example noting video views may matter more to the north star than desktop comments, before recommending a next step.
Common mistakes
- Assuming the feature directly caused the desktop drop without checking for cannibalization or coincidence.
- Treating mobile and desktop metrics as unrelated instead of checking for user migration between them.
Likely follow-up questions
- How would you determine if this is a net positive change?
- What additional data would you pull before deciding to keep the feature?
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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