Definition
A PQL is a lead identified by product usage signals (not only form fills). PQLs often convert better when the product is the primary driver of value.
Example
A user invites two teammates and connects a data source; the account becomes a PQL.
How to use it
- Define PQL events that correlate with retention, not vanity actions.
- Track PQL-to-paid conversion by cohort and segment.
- Use a minimum usage window to avoid tagging one-off spikes as PQLs.
Common mistakes
- Using single clicks or page views as PQL criteria.
- Changing PQL definitions without re-baselining conversion rates.
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 "PQL (Product-Qualified Lead)" 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.
- Use a calculator that references this term (e.g., PQL to Paid Conversion Calculator) to sanity-check assumptions.
- Read the related guide (e.g., PQL to paid: how to define PQLs and track conversion to revenue) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- PQL to Paid Conversion Calculator: Compute PQL-to-paid conversion rate and the number of paid customers implied by PQL volume.
Guides
- PQL to paid: how to define PQLs and track conversion to revenue: A practical guide to PQL-to-paid conversion: define predictive PQL events, measure cohorts, and use segmentation to improve conversion and retention.
- 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.