Definition
Product adoption measures how deeply and broadly customers use your product (features, frequency, breadth of teams). It is a driver of retention and expansion.
Example
An account uses three core features weekly across two teams, signaling high adoption.
How to use it
- Track adoption by cohort and by segment; blended adoption hides weak cohorts.
- Tie adoption metrics to retention outcomes to avoid vanity usage metrics.
- Separate breadth (how many features) from depth (how often) to see gaps.
- Monitor adoption drop-offs after releases to catch regressions.
Common mistakes
- Using logins as a proxy for adoption without feature usage context.
- Aggregating adoption across very different personas.
Why this matters
This term matters because small changes compound in SaaS metrics. Use consistent definitions by cohort and segment so you can diagnose retention, payback, and growth quality.
Practical checklist
- Write a 1-line definition for "Product Adoption" that your team will use consistently.
- Keep the time window consistent (weekly/monthly/quarterly) when comparing trends.
- Segment results (channel/plan/cohort) before drawing big conclusions from blended averages.
- Sanity-check with a related calculator from the same category on MetricKit.
- Read the related guide (e.g., PLG metrics hub: activation, trial conversion, stickiness, and adoption) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- DAU/MAU (Stickiness) Calculator: Compute DAU/MAU stickiness and translate it into implied active days per month.
- WAU/MAU Calculator: Compute WAU/MAU and translate it into implied active weeks per month.
- Feature Adoption Rate Calculator: Compute feature adoption: what % of active users used a specific feature in a time window.
- PQL to Paid Conversion Calculator: Compute PQL-to-paid conversion rate and the number of paid customers implied by PQL volume.
- Gross Margin Impact Calculator: Quantify how gross margin changes affect gross profit LTV, payback, and LTV:CAC (before vs after).
Guides
- PLG metrics hub: activation, trial conversion, stickiness, and adoption: A practical hub for product-led growth metrics: activation rate, trial-to-paid, DAU/MAU and WAU/MAU stickiness, feature adoption, and PQL-to-paid conversion.
- Cohort analysis playbook: retention curves, LTV forecasting, and payback: A practical cohort analysis workflow: build retention curves, forecast LTV, and translate retention quality into payback and growth decisions.