Metrics question
For a new Enterprise Intelligence product at Glean, what metrics would you define to determine whether it is creating real value for leaders and teams? Distinguish clearly between adoption, insight quality, actionability, and business outcome metrics, and explain how you would avoid over-weighting vanity usage signals.
- Glean
- Metrics
- Medium
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What this question tests
Whether you can define outcome-focused metrics for a leadership-facing insight product and explicitly avoid rewarding usage that looks impressive but does not reflect real decision impact.
How to approach it
- Adoption metrics: percentage of target leaders (like VPs or department heads) actively viewing insights weekly, and breadth of teams represented in generated insights.
- Insight quality metrics: percentage of insights confirmed accurate by the leader reviewing them, and rate of insights flagged as already known or not useful.
- Actionability metrics: percentage of insights that result in a documented action, like a follow-up task, policy change, or team conversation, tracked through a lightweight in-product action log.
- Business outcome metrics: change in the specific metric an insight was about, for example team attrition risk flagged and then actually addressed, measured over the following quarter.
- Avoid over-weighting vanity signals by not treating dashboard views or time spent as success on their own, since leaders can passively view without ever acting, and instead anchor primarily on the actionability and business outcome layers.
What a strong answer includes
- Separates four distinct metric categories, adoption, insight quality, actionability, business outcome, matching exactly what the question asks for.
- Names a concrete actionability mechanism, a lightweight action log, rather than just asserting insights are actionable.
- Explicitly calls out dashboard views and time spent as vanity signals to avoid over-weighting, directly answering the stated concern.
Common mistakes
- Uses views or session time as a primary success metric, which is exactly the vanity signal the question warns against.
- Lists adoption and quality metrics but never defines a real business outcome metric tied back to what the insight was about.
Likely follow-up questions
- How would you attribute a business outcome change specifically to the insight versus other factors.
- What would you do if leaders view insights regularly but rarely log any action.
More metrics questions
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- Glean cares about time-to-first-call, integration success rate, and API error rates. Which metrics would you treat as the core indicators that external developers are actually reaching production successfully, which are just supporting diagnostics, and how would you instrument the platform to measure the funnel from initial setup to a live production integration?Glean · Metrics · Medium
- Glean wants customers to safely compare multiple LLMs before committing one to production. What end-user workflow and admin/API capabilities would you prioritize in v1, what would you leave out, and how would you measure whether the experimentation experience is actually helping customers make better rollout decisions?Glean · Metrics · Hard
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More questions from Glean
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