MODULE 11
Discovery Metrics
Measure the health and output of your discovery process itself.
What to Measure in Discovery
Two Kinds of Metrics
- Outcome metrics — the business/customer results discovery is meant to drive (activation rate, retention, revenue per user).
- Process metrics — signals about whether discovery itself is happening well (cadence, evidence quality, decision speed).
Useful Process Metrics
- Customer contact frequency — are you talking to users at least weekly?
- Assumptions tested per cycle — how many leap-of-faith assumptions get validated or killed per sprint/month?
- Idea-to-evidence time — how long from "we have an idea" to "we have real evidence about it"?
- % of roadmap items backed by evidence vs. opinion-driven.
Useful Outcome Metrics
- Activation rate — % of new users reaching a meaningful first-value moment.
- Retention/churn — are users sticking around?
- Feature adoption — % of target segment using a newly shipped solution.
- North Star Metric — one metric that best captures the core value delivered to customers, used to align all discovery work.
Avoiding Vanity Metrics
Metrics like "number of features shipped" or "number of interviews conducted" measure activity, not impact. Always connect process metrics back to whether they're improving outcome metrics over time.
Building a Metrics Dashboard
Pair a small set of outcome metrics with the process metrics that predict them, reviewed on a regular cadence (e.g. biweekly) so the team can course-correct discovery habits, not just react to results months later.
Module Quiz
Answer all 5 questions and submit to check your understanding.
1. Outcome metrics primarily measure:
2. Which is a process metric for discovery health?
3. A North Star Metric is best described as:
4. Why is 'number of interviews conducted' often a vanity metric on its own?
5. What does '% of roadmap items backed by evidence' help reveal?