Strategy question
How would you go about ranking posts and everything else on Newsfeed?
- Meta
- Strategy
- Hard
Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.
Start a mock interview on this question · Mock interview from a job description
What this question tests
Deep product sense on ranking systems, checking whether you can name the actual objective function trade-offs behind a feed, not just say 'show relevant content'.
How to approach it
- Clarify scope: organic posts, ads, and Groups or Marketplace content all compete for the same feed real estate, so define which is in scope.
- State the ranking objective: predict and maximize meaningful engagement, weighted toward close friends and family over public pages, per Meta's own stated shift.
- List the signal inputs: post type, poster relationship strength, historical engagement with similar content, recency, and predicted watch or comment likelihood.
- Address the trade-off between engagement-maximizing content, which skews sensational, and long-term wellbeing, which Meta has been penalized for ignoring before.
- Propose a scoring model that blends predicted engagement with a wellbeing or diversity penalty, then re-ranks for variety across content types.
- Define success with a balanced scorecard: session time, meaningful interactions, and a survey-based satisfaction score, not engagement alone.
What a strong answer includes
- Names the real historical trade-off Meta faced, engagement-maximizing ranking driving misinformation and outrage, and designs around it explicitly.
- Proposes a concrete scoring approach, weighted signals plus a penalty term, rather than a vague 'use machine learning' answer.
- Uses a balanced metric set instead of raw engagement, reflecting awareness of Meta's past ranking controversies.
Common mistakes
- Describing ranking as simply 'most relevant content first' without naming the actual signals or trade-offs.
- Ignoring the wellbeing and misinformation risks that make pure engagement-maximization dangerous for Meta specifically.
Likely follow-up questions
- How would you measure 'meaningful' interactions versus passive ones?
- How would you prevent this ranking model from amplifying misinformation?
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More questions from Meta
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