Metrics question
What should be the goal for Facebook Live?
- Meta
- Metrics
- 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.
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What this question tests
Ability to set a clear, defensible goal for a specific product surface, grounded in what that surface is actually for.
How to approach it
- Clarify Facebook Live's purpose within Meta's broader video strategy: real-time, authentic connection, distinct from polished on-demand video like Reels.
- Identify who uses it today: creators and public figures doing real-time Q&A or events, and everyday users sharing live moments with friends.
- Propose the goal should center on live engagement quality, not raw watch time, since the value of live is interaction, not passive consumption.
- Define the goal concretely: grow concurrent live viewership with meaningful interaction, like comments or reactions per live session, not just stream count.
- State a guardrail: broadcaster retention, since Live only works if creators keep coming back to go live.
What a strong answer includes
- Picks a goal specific to what makes live video valuable, real-time interaction, rather than reusing a generic video-watch-time goal.
- Distinguishes Live from Reels explicitly, showing awareness that they serve different jobs within the same platform.
- Names both a viewer-side engagement goal and a broadcaster-side retention guardrail, since Live is a two-sided feature.
Common mistakes
- Setting a goal identical to any other video product, like total watch time, ignoring what's distinctive about live.
- Ignoring the broadcaster side entirely, when Live has no value without people willing to go live.
Likely follow-up questions
- How would you measure interaction quality beyond just comment count?
- How would you grow the broadcaster base without spamming users with irrelevant live notifications?
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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 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