Free Returns ROI Calculator

Last updated: September 2026

Should You Offer Free Returns on Shopify? The 2026 ROI Calculator

Use the formulas below as a worksheet to compare two policies. Copy the inputs into your own spreadsheet or calculate them directly. The worked example uses illustrative values, not measured merchant results or a forecast.

Define the policy before entering numbers

Write down which orders qualify, the return window, who pays return transport, and whether refunds, exchanges and final-sale items have different conditions. Model the same customer segment and reporting period under each policy. A policy that changes several conditions needs assumptions for each affected cost.

Use contribution instead of refunded revenue

For a retained order, start with sales revenue and subtract product cost, outbound shipping, payment fees and variable fulfilment costs. Enter the resulting contribution per retained order.

For a fully returned order, enter the net loss: unrecovered outbound costs, return transport, handling, non-refundable fees and unrecoverable product value, less any return fees retained. Refunded revenue is not an additional expense in this calculation, and recovered inventory value should not be charged again. This worksheet models returned-order losses of zero or more.

Enter policy costs that do not scale per order separately for the same reporting period. Avoid counting these costs both in per-order amounts and in the fixed-cost field.

Calculate both scenarios

Use fractions for conversion and returned-order rate in these formulas: 2% is 0.02 and 10% is 0.10.

1. Expected contribution per order = (1 − returned-order fraction) × retained-order contribution − returned-order fraction × returned-order loss.
2. Period contribution = visits × conversion fraction × expected contribution per order − fixed policy costs.
3. Change in contribution = proposed period contribution − current period contribution.

A positive change means that the proposed policy performs better under the assumptions entered. It does not show that customers will convert at the assumed rate.

Worked example: a small gain can become a loss

Suppose a store has 10,000 visits in a period. Under its current policy, conversion is 2%, 10% of orders are fully returned, retained-order contribution is 30 currency units, returned-order loss is 8, and fixed policy cost is zero.

Expected contribution per order is (0.90 × 30) − (0.10 × 8) = 26.20. The 200 orders therefore contribute 5,240.

For the proposed policy, assume conversion of 2.3%, a 15% fully returned-order rate, retained-order contribution of 30, returned-order loss of 12 and fixed costs of 100. Expected contribution per order is (0.85 × 30) − (0.15 × 12) = 23.70. The 230 orders contribute 5,451 before fixed costs, or 5,351 after them: an increase of 111.

Keep the other proposed inputs unchanged but increase the returned-order rate to 25%. Expected contribution per order becomes 19.50, period contribution becomes 4,385, and the change becomes −855. This is a sensitivity example, not an industry benchmark.

Find break-even conversion

When proposed expected contribution per order is positive, divide current period contribution plus proposed fixed costs by visits multiplied by proposed expected contribution per order. Multiply the result by 100 to express conversion as a percentage.

In the example, (5,240 + 100) ÷ (10,000 × 23.70) gives approximately 2.2532% conversion. That is the proposed conversion rate needed to match current contribution while holding the other inputs fixed.

If proposed expected contribution per order is zero or negative, more orders cannot improve contribution in this model. If the required conversion exceeds 100%, the proposed scenario cannot match the baseline with the entered assumptions.

Measure a complete order cohort

Choose orders placed during a defined period and allow their return window to finish. Keep visits, orders, returned orders and costs aligned to that population. A recent group of orders with incomplete returns will understate the final return rate.

Keep exchanges and partial returns separate: this worksheet models fully retained and fully returned orders. Tax, overhead not entered, repeat purchases and lifetime value are outside its result. It reports contribution and break-even conversion, not an investment ROI percentage.

Run conservative and optimistic assumptions before changing a policy. After a controlled trial, replace assumptions with observations. Traffic mix, promotions and seasonality can also change conversion; an overall before-and-after increase does not establish that free returns caused it.

Frequently asked questions

Should my Shopify store offer free returns?

Compare your current and proposed contribution using your own costs and a range of conversion and returned-order assumptions. There is no universal profitable order value or return rate.

Does this calculation predict conversion uplift?

No. You enter both conversion rates. The calculation shows their conditional contribution and the conversion required to match the current scenario.

Does this model exchanges and partial returns?

No. It splits orders into fully retained and fully returned orders. Model exchanges and partial returns separately before treating the result as a complete view of your business.

Does this determine refund timing or Forthroute fees?

No. The worksheet does not process returns or determine refund timing. Review Forthroute pricing and enter the applicable costs for your own workflow.

Next step

Calculate both scenarios using the formulas above, then identify which assumption most changes the result. For the wider workflow, read the Shopify returns management guide.