Calculator

Refund Rate Breakeven Calculator

Break-even ROAS gets softer the moment return pressure is pulled into the order. Use this calculator when the ads look acceptable on paper but refund behavior is likely pushing the real acquisition ceiling lower than the team thinks.

Start from real contribution before ads
Add refund drag back into the ROAS line
See how returns shift the true customer acquisition ceiling

Calculate refund-adjusted break-even ROAS

Enter AOV, product cost, fulfilment, fee rate, variable cost, refund rate, return shipping, and restocking drag. The result shows how the break-even ROAS changes once refund pressure is treated as part of the order economics.

Average order value Gross order value before refund pressure. Product cost Direct product or COGS for the order. Fulfilment cost Outbound fulfilment and shipping cost. Fee rate % Marketplace or payment drag on revenue. Other variable cost Packaging, inserts, or similar variable cost not already listed. Refund rate % Expected share of orders that end up refunded or returned. Return shipping cost Reverse logistics burden on refunded orders. Restocking cost Inspection, refurbishment, or repackaging drag.

Three refund-pressure scenarios.

Formula

What the refund-adjusted model changes

Refund-adjusted contribution = Baseline contribution before ads - Expected refund drag

Return-adjusted break-even ROAS = Average order value / Refund-adjusted contribution

Standard ROAS math assumes the order lives as sold. This model relaxes that assumption by charging the original order with expected refund drag, reverse logistics, and restocking pressure before traffic targets are judged.

Where teams underprice traffic

They set ROAS targets before accounting for refund-heavy categories.
They treat return shipping as a service issue, not an ad-efficiency issue.
They read contribution from the sold order and stop there.

Useful next step

Once the return-adjusted ROAS is clear, compare it against the standard ROAS view and the broader return-rate profit model so refund pressure sits in the same decision chain as traffic.