Strategy question
Discuss the tradeoffs between showing the "people you may know" widget versus ads in the newsfeed. How would you decide which one to show to a given user?
- Meta
- Strategy
- Hard
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What this question tests
Ranking and monetization tradeoff thinking, balancing user engagement value against ad revenue in a single feed slot.
How to approach it
- Clarify the tension: each feed slot given to People You May Know is a slot not sold as an ad, a direct revenue tradeoff.
- Assess user value: PYMK drives network growth and long-term engagement, while ads drive immediate revenue but can fatigue users if overused.
- Segment by user state: new users with few connections benefit more from PYMK, while established users with large networks get less value from it.
- Propose a decision rule: show PYMK more to users below a connection count threshold, and prioritize ads more for well-connected long-tenured users.
- Add a guardrail: cap ad load per session so revenue optimization does not degrade retention long term.
- Success metric: balance long-term network growth (a leading indicator of future engagement and ad inventory) against short-term ad revenue per session.
What a strong answer includes
- Frames PYMK as an investment in future engagement and future ad inventory, not just a cost against current revenue, a key strategic insight.
- Segments the decision by user connection count, a concrete, implementable targeting rule.
- Sets a guardrail on ad load to protect long-term retention rather than optimizing only for short-term revenue.
Common mistakes
- Treating this as a simple more ads equals more revenue decision with no long-term retention consideration.
- No segmentation of which users need PYMK most.
- Ignoring that PYMK today drives ad inventory growth tomorrow through a larger network.
Likely follow-up questions
- How would you quantify the long-term value of a new connection made through PYMK?
- What connection count threshold would you use to decide, and how would you validate it?
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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