How Return Abuse Works — and How to Spot It on Shopify

Returns are a normal cost of selling online. Return abuse is different: it's the slice of returns that isn't honest, and it comes straight off your margin. The tricky part is that abuse and legitimate behavior look similar on a single order — you can only see it across a customer's history.

The patterns worth knowing

• Wardrobing — buying, using, and returning. Shows up as a high return ratio on used-looking goods.
• Serial returning — returning most of what they buy, quarter after quarter.
• Refund without return — a refund issued where the merchandise never came back. The purest hard loss.
• "Item not received" claims against a signed, scanned delivery.
• Chargeback double-dip — a refund, then a chargeback on the same order, so you pay twice.

Why the moment of decision is the problem

The call gets made in the return queue, where the customer's past twelve months aren't visible. Without history at that moment, you either approve everything (and eat the loss) or risk accusing a good customer — which costs far more than the refund.

Surface risk without accusing anyone

The healthier approach is to score each return for risk, show the exact signals behind the score, and let a human decide — never auto-decline. Bracketing three sizes of a shoe should score low; a third damage claim in six months plus prior refunds that never came back should surface for review.

That's the philosophy behind Return Intelligence: explainable 0–100 scoring, a free 12-month leakage audit, and no automatic declines. Start with the Return Intelligence overview.