When returns get expensive, the tempting fix is a rule for everyone. That charges your best customers for the behavior of a few. The better fix is to find the few.

Three different problems

• Fraud: stolen goods, empty boxes, a cheaper item sent back. Handled with evidence.
• Abuse: wearing an outfit to an event and sending it back (wardrobing), or returning used goods as new.
• Heavy returning: bracketing sizes, trying on at home. Allowed, often a keen customer, but past some rate every order loses money.

The industry numbers come from companies that sell fraud prevention, so treat them as direction. Appriss Retail estimates that of $706 billion in US returns in 2025, $100 billion was preventable loss from fraud and abuse, with abuse costing about six times as much as fraud Reported. Narvar, another returns vendor, says more than 90% of return fraud and abuse comes from less than 3% of shoppers, without publishing its method Reported. The shape is consistent: the cost concentrates in a small group.

Where to draw the line

Draw it with your own margin, not a competitor’s rule. A customer earns you margin on what they keep and costs you shipping on everything, plus handling and write-offs on what comes back. Above some return rate, every order they place loses money. The tool finds that rate, then asks what friction above it would do.

With the defaults, an order loses money once a customer sends back more than about 66% of orders. The 400 customers at 75% each cost $51.90 a year. A $5 fee on their returns, even if it loses 30% of their orders, turns them into $54.35 a year each: about $42,500 more across the group. Now set both return rates to 40%, a heavy but profitable customer the fee doesn’t change: the same friction costs about $14,150 a year. That’s the case against blanket fees in one number.

A case: ASOS

ASOS, the UK online fashion retailer, shows a targeted rule in public. From October 2024 it began deducting £3.95 from refunds for customers with a frequently high return rate who keep less than £40 of an order, while most customers kept free returns Reported. Its fair use policy sets the line at a return rate of 70% or more by value over twelve months, with at least three orders; guest orders always pay; and customers whose rate falls go back to free returns automatically Reported. In January 2026 it began showing each customer their own return rate in the app Reported.

The design has the parts that matter: a line set by data, a rule the customer can see, and a route back. UK law keeps faulty items out of it regardless (chapter 13).

Warn before you charge, charge before you ban, and ban only with evidence.

A ladder of responses

1. NothingFor almost everyone.
2. A plain noteFor customers nearing the line: their rate, what the line is, and what changes if they cross it. Appriss says 90% of consumers buy again after receiving a warning Reported, vendor data again, but a note costs nothing to test.
3. Refund at inspectionAbove the line: no instant exchange or refund-at-scan. Slower money, same policy.
4. A fee, or no free labelAbove the line, applied by rule, disclosed in advance, never on faulty items.
5. Closing the accountOnly for fraud, with evidence, and reviewed by a person.

For wardrobing in occasionwear, a large tag that must be attached for a return to be accepted does more than any customer rule. Whatever you automate, have counsel check it against privacy law; automated decisions about individuals are regulated in the EU and UK.

Do this

• Run the tool with your margins to find your line. Count the customers above it in the last twelve months, and look at ten of them by hand before writing any rule. Then start with step 2 of the ladder.