Refund Rate Calculator
The refund rate calculator measures the share of completed orders that were refunded in a defined cohort and reporting period.
How to use this calculator
- Enter completed orders and the subset of those orders that were refunded.
- Check the units and definitions before comparing results with another source.
- Change one input at a time when comparing scenarios, and keep the reporting period and assumptions consistent.
Formula used by the refund rate calculator
Refund rate = refunded orders ÷ completed orders × 100%
- Refund rate = refunded orders ÷ completed orders × 100%
- Count unique refunded orders consistently. This metric does not account for refund value, partial refunds, chargebacks or why refunds happened.
- Inputs are checked for required values and valid ranges; displayed results are rounded for readability.
Worked examples
Worked example
Twenty-four refunded orders from 850 completed orders.
24/850 × 100 ≈ 2.82% refunded orders.
24/850 × 100 ≈ 2.82% refunded orders.
Understanding the result
The refund rate calculator measures the share of completed orders that were refunded in a defined cohort and reporting period.
Count unique refunded orders consistently. This metric does not account for refund value, partial refunds, chargebacks or why refunds happened.
Important notes
Count unique refunded orders consistently. This metric does not account for refund value, partial refunds, chargebacks or why refunds happened.
The result applies to the numbers and assumptions entered here; verify specifications for safety-critical or regulated uses.
Frequently asked questions
Is order refund rate the same as revenue refund rate?
No. Order rate weights each order equally; revenue-based measures compare refunded amount with sales revenue.
How should periods be compared?
Use the same order definition, refund window and reporting method in every period.
How do I use this calculator?
Enter completed orders and the subset of those orders that were refunded.
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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.