Strategy question
Suppose you're the PM for Facebook Stories and your teammate says we should increase the height of the stories bar in the app. How would you think through this decision?
- Meta
- Strategy
- Medium
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What this question tests
Tests pushing back constructively on an unvalidated design suggestion using a hypothesis-and-test framework rather than agreeing or dismissing outright.
How to approach it
- Ask what problem the teammate believes this solves, for example low Stories discovery or engagement, before evaluating the specific solution.
- State the hypothesis explicitly: a taller bar increases visual prominence, which could raise tap-through rate but also pushes feed content further down.
- Identify the tradeoff: any gain in Stories engagement must be weighed against potential loss in Feed engagement from the added visual real estate taken.
- Propose an A/B test comparing the taller bar against the current height, measuring both Stories tap-through and overall Feed engagement together.
- Decide based on the net effect across both surfaces, not Stories engagement in isolation, before rolling out any change.
What a strong answer includes
- Reframes a design opinion as a testable hypothesis instead of simply agreeing or disagreeing based on intuition.
- Explicitly names the tradeoff, Stories gain versus Feed real estate loss, that a single-metric view would miss.
- Insists on measuring net platform impact, not just the metric the change was intended to move.
Common mistakes
- Agreeing to make the change purely on a teammate's intuition without validating the underlying problem.
- Measuring only Stories engagement without checking the impact on Feed engagement below it.
Likely follow-up questions
- How would you size the test to detect a small but real engagement change?
- What would make you reject this idea even if Stories engagement went up?
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Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop