What Is a Product Qualified Lead?
A product qualified lead is a prospect who has used your product enough to demonstrate clear purchase intent through specific actions. Most teams export their PQL list weekly — but the CSV typically contains raw event counts rather than the scored, normalized signals that actually drive decisions.
See exactly which product usage columns to pull into your scoring model and how to weight them in a spreadsheet.
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Upload your spreadsheet.xlsx .xls .csv — free to try, no accountWhat this export contains
| user_id |
| plan_type |
| events_last_30_days |
| feature_flags_enabled |
| sessions_last_week |
| invite_sent |
| export_count |
| last_active_date |
| onboarding_complete |
| trial_days_remaining |
What usually goes wrong with it
Raw event counts without context
The export shows total events_last_30_days but not which events matter — a user who triggered 50 low-value actions scores the same as one who used the core feature twice.
DataMimi Datamimi reads the events_last_30_days column and lets you apply per-event weights in a formula column alongside the raw data.
Missing scoring weights
Columns like invite_sent and export_count are equally weighted by default, but inviting a colleague signals 5x more intent than running an export.
DataMimi It surfaces invite_sent and export_count as separate scored dimensions so you can weight each independently in the model.
No decay on recency
last_active_date sits unused in column H while scores are calculated from lifetime totals, making a user who churned 60 days ago look hotter than yesterday's active user.
DataMimi It calculates a recency-decayed score from last_active_date using a built-in decay formula applied across the row.
Trial vs paid signals mixed
plan_type is there but analysts rarely segment scoring by trial vs paid expansion, causing sales to call the wrong users.
DataMimi It filters by plan_type automatically so trial PQLs and expansion PQLs flow into separate ranked lists.
Common questions
What is a product qualified lead?
A product qualified lead (PQL) is a user who has hit a usage milestone — such as completing onboarding, inviting a teammate, or exporting data — that your team has identified as predicting conversion to paid.
How is a PQL different from an MQL?
A marketing qualified lead is scored on demographic and behavioral signals before product use; a PQL is scored on actual in-product behavior, making it a stronger signal for product-led growth companies.
What columns should a PQL scoring model include?
Essential columns include event counts for core features, invite or sharing actions, recency signals like last_active_date, plan type, and trial days remaining.
What is a good PQL threshold?
Most teams start with a threshold tied to their top-converting usage pattern — if users who export three times convert at 40%, set export_count ≥ 3 as a required criterion.
How much does Datamimi cost?
Datamimi offers a Free plan at $0/month (40 credits, no credit card required), Lite at $9/month (400 credits), Starter at $24/month (1,500 credits, up to 3 simultaneous files), Pro at $59/month (5,000 credits with rollover), and Team at $199/month (20,000 credits, 5 users).
Try it with your own file
DataMimi reads the file you actually have — merged cells, headers below row one, totals pasted at the bottom — and shows which rows and columns every number came from.
Ask about your file