Product Health Metrics
Separate vanity usage from signals that predict retention and expansion.
Metrics in this guide
Each card defines one metric — what it measures, how to calculate it, and a typical benchmark.
- Validation
Activation
Activation rate
Share of new users who reach a defined “aha” or value action.
- Formula
- Users completing activation event ÷ new signups
- Typical benchmark
- Define activation per product; 25–40%+ is strong for PLG trials.
- Validation
TTV
Time to value
Median time from signup to first meaningful outcome.
- Formula
- Median hours/days to activation event
- Typical benchmark
- Shorter TTV correlates with higher retention in most B2B SaaS.
- Validation
Retention
Cohort retention
Share of a signup cohort still active after N days or weeks.
- Formula
- Active users in cohort at week N ÷ cohort size
- Typical benchmark
- Look for flattening curve; compare W4/W8/W12 by segment.
- Execution
DAU/MAU
DAU / MAU ratio
Daily active users divided by monthly active users — stickiness.
- Formula
- DAU ÷ MAU
- Typical benchmark
- Consumer 20%+ strong; B2B workflow tools vary widely by role.
- Execution
Adoption
Feature adoption depth
Share of active users using features that predict retention.
- Formula
- Users of predictive feature ÷ WAU or MAU
- Typical benchmark
- Identify 2–3 “retention features” from cohort analysis.
Product health metrics measure whether users reach value and stay: activation rate, time-to-value (TTV), cohort retention (D1/D7/D30/W4), DAU/MAU, and feature adoption depth.
Revenue lagging indicators hide product problems. Health metrics show if execution delivers the promise before GTM scales.
After launch, during onboarding redesign, or when /funnel shows leaks. Feeds /pmf and experiment prioritisation.
- Define activation (meaningful action, not signup).
- Measure TTV median and p90.
- Plot retention curves by cohort and segment.
- Add engagement ratio (DAU/MAU or weekly active).
- Track 2–3 features that predict retention.
- Compare to
/northstar— health should predict NSM movement.
- Cohort curves flatten above zero.
- Activation definition stable quarter to quarter.
- Login counts as activation.
- Mixing mobile and web cohorts.
- Optimising engagement that does not correlate with retention.
Northvale portal. Activation: 62% complete onboarding ≤14 days; TTV 9 days median; D30 retention 78% active suppliers; feature adoption doc-upload wizard 71%. Read: activation is bottleneck — aligns with /funnel diagnosis.
PulseWell. Activation: 54% connect HRIS; TTV first nudge in 5 days; W4 retention 61% managers; DAU/MAU 0.38. Read: HRIS connect is critical path — matches funnel leak hypothesis.
Harbor diagnostic product. Activation: 88% complete diagnostic; TTV report in 48h; repeat use 22% run second diagnostic within 6 months. Productised SKU health separate from consulting NPS.
Clearwater check-ins. Activation: 94% volunteers send first check-in; 30-day retention 71% sites compliant; TTV first donor report in 30 days. Field bandwidth caps — watch seasonal dropout.
Run /funnel for step diagnosis; /northstar for the outcome metric; /pmf when testing fit. Use /datastrat to wire events.
Related techniques
Sources & further reading
- Chen, A. (2021). The Cold Start Problem. Harper Business.