PQL to Paid Conversion Calculator
Compute PQL-to-paid conversion rate and the number of paid customers implied by PQL volume.
PQLs (product-qualified leads) are users/accounts that show product usage signals correlated with conversion and retention.
Tracking PQL-to-paid conversion helps connect product usage to revenue outcomes and improves prioritization between activation and sales follow-up.
Prefer an explanation- Read the guide.
PQL to paid: how to define PQLs and track conversion to revenuePLG metrics hub: activation, trial conversion, stickiness, and adoptionTrial-to-paid conversion: definition, formula, and how to improve itFeature adoption rate: definition, how to measure adoption, and pitfalls
Set 0 to disable target rate calculation.
Tip: you can type commas (e.g., 10,000).
Example
Using the default inputs, the result is:
10%
- PQLs
- 900
- Paid customers from PQLs
- 90
- Target paid customers (optional)
- 120
How to calculate
- Enter PQLs generated in a period/cohort.
- Enter paid customers that originated from those PQLs (same window definition).
- Optionally enter a target paid count to compute required PQL-to-paid rate.
Formula
PQL-to-paid = paid customers from PQLs / PQLs
- PQL definition is stable and predictive (not vanity).
- Paid customers are attributed back to the originating PQL cohort consistently.
FAQ
What should define a PQL-
Use product signals that correlate with conversion and retention (e.g., invited teammates, created X items, integrated Y). Validate PQL definitions by cohort outcomes.
Should I track PQL-to-paid by channel-
Yes. PQL quality varies by channel and persona. Segmenting helps you invest in channels that produce PQLs that convert and retain.
Common mistakes
- Defining PQLs using vanity actions (not predictive of retention).
- Mixing cohorts (PQLs from one month, paid conversions from another).
- Not separating self-serve vs sales-assisted conversion paths.
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Quick checks
- Keep time units consistent (monthly vs annual) across inputs and outputs.
- Segment by cohort/channel/plan before trusting a blended average.
- Use the related guide to avoid common definition and denominator mismatches.