Conversion Funnel Drop-Off Calculator
Funnel drop-off measures how many entrants do not reach the next defined stage. It complements progression rate when reviewing an onboarding or sales flow.
How to use this calculator
- Enter entrants and those advancing from the same funnel stage and period.
- Check that all inputs use the same units, period and population scope.
- Change one assumption at a time when comparing scenarios.
Formula used by conversion funnel dropoff calculator
Drop-off count = entrants − advanced; drop-off rate = drop-off count ÷ entrants × 100%.
- Drop-off count = entrants − advanced; drop-off rate = drop-off count ÷ entrants × 100%.
- Counts should use a clear identity and attribution window. Repeat visits and multi-device journeys can change the result.
- The tool validates inputs and rounds displayed figures for readability; it does not validate assumptions against external records.
Worked examples
Worked example
3,200 sessions enter a stage and 640 progress.
3,200 − 640 = 2,560 drop-offs; rate = 80%.
The stage drop-off rate is 80%.
Understanding the result
Funnel drop-off measures how many entrants do not reach the next defined stage. It complements progression rate when reviewing an onboarding or sales flow.
Counts should use a clear identity and attribution window. Repeat visits and multi-device journeys can change the result.
Important notes
Counts should use a clear identity and attribution window. Repeat visits and multi-device journeys can change the result.
Treat the result as an estimate from the entered assumptions. For safety, legal, engineering, health or commercial decisions, verify relevant specifications and professional guidance.
Frequently asked questions
Is drop-off the same as bounce rate?
No. Bounce definitions vary by analytics platform; funnel drop-off is based on a specific next-stage transition.
Does this tell me why users left?
No. Combine it with qualitative feedback and segment analysis to investigate reasons.
How should I interpret this result?
Counts should use a clear identity and attribution window. Repeat visits and multi-device journeys can change the result.
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This page provides a calculation tool plus explanatory information so you can understand what the result means and when the underlying method may not fit your situation.