Metrics question
What are the top 3 metrics you would track for Quora?
- Quora
- Metrics
- Easy
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What this question tests
Whether you can select metrics that reflect a Q&A platform's core value, content quality and knowledge exchange.
How to approach it
- Clarify the business goal being measured, likely growing engaged users who both ask and answer questions.
- Prioritize a content quality metric, like percent of questions receiving a high-quality answer within a set time, since that's the platform's core promise.
- Track a contributor health metric, like active answerer retention, since content supply depends on repeat contributors, not just askers.
- Track a satisfaction metric, like upvote ratio or answer helpfulness rating, to confirm quality is being maintained, not just volume.
- Explain why each metric was chosen relative to Quora's specific value proposition, knowledge sharing, not generic engagement.
- Note a guardrail to consider, like spam or low-quality answer rate, that would undercut the primary metrics if ignored.
What a strong answer includes
- Chooses metrics tied specifically to Quora's core value, quality answers, rather than generic engagement metrics like DAU.
- Includes a contributor-side metric, answerer retention, recognizing content supply is the platform's real bottleneck.
- Explains the reasoning behind each metric choice relative to the product's actual value proposition.
- Flags spam or low-quality answer rate as an implicit guardrail worth watching alongside the top 3.
Common mistakes
- Picking generic metrics like DAU or session time that don't reflect Quora's specific value, quality knowledge sharing.
- Ignoring the contributor side entirely and only measuring metrics about people asking questions.
Likely follow-up questions
- How would you measure answer quality at scale without manual review of every answer?
- Which of these 3 metrics would you prioritize if you could only track one?
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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