Apparel
·
Lookback
A 10% return rate hid three abuse patterns. Fixing them projects to $230K+ a year at 5x ROI.
A lookback across about 500K orders a year at a multi-brand fashion retailer. Wardrobing, bracketing and coupon abuse were running at once, and every refund was handled by hand.
projected annual savings
projected cut in return fraud
of returns could clear with no review
The challenge
Half of all returners came back more than once
This multi-brand fashion retailer ships about 500K orders a year at an average order of roughly $140, with about 10% of sales by value coming back. Fashion invites three kinds of abuse at once: wardrobing, where an item is worn and then returned; bracketing, where several sizes are bought to keep one; and coupon abuse through new accounts. All three were running together. Half of all returners had returned from more than one order, yet the returns team processed every refund by hand. Abusive and genuine returns waited in the same queue, enforcement depended on whoever happened to spot a pattern, and loyal customers paid for it with slower refunds. Worn items that could no longer be sold as new went to markdown or liquidation.
What Pinch found
Three abuse patterns, one manual queue
Scoring every historical order and return pulled the three patterns apart. Bracketed orders came back at 4x the store average, with 40% of bracketed items returned. Coupon abuse traced back to single people behind several emails, using identical shipping and billing addresses and discounts on more than 70% of their orders. Wardrobed items came back worn and often could not be sold as new. Because all of it sat in the same manual queue as genuine returns, none of it was being stopped, and good customers waited just as long as abusers.
Projected annual savings from stopping abusive returns and stacked discounts.
Projected reduction in return fraud once abusers are scored and routed before refund.
Projected lift in VIP retention from instant refunds and free returns.
Of returns could clear with no manual review.
Pinch recommended scoring every return before refund. The score decides what the customer is offered and what the warehouse does with the parcel.
The response
Friction for abusers, instant refunds for everyone trusted
Pinch recommended deciding how each return is handled based on who is sending it. High-confidence wardrobers would lose return privileges, and parcels from suspects would go to a separate warehouse inspection instead of straight back to stock. Multi-size orders would be flagged before they ship, with sizing help sent to the customer. Linked coupon accounts would be blocked and stacked discounts cancelled. VIPs would get instant refunds, free returns, longer windows and exchange rebates.
Wardrobers
Block
Deny returns from high-confidence abusers, cancel future orders and route suspect parcels to a separate inspection.
Bracketers
Friction
Flag multi-size orders before they ship and send sizing help.
Coupon abuse
Block
Block linked accounts and cancel stacked discounts automatically.
Best customers
Reward
Instant refunds, free returns, longer windows and exchange rebates.
How Pinch worked
One risk score from return request to warehouse dock
Pinch scored every order and return in the brand's history on 100 risk signals and resolved linked accounts to the person behind them, so three emails sharing one address read as one customer. The recommendation carries that score through the whole return: it sets the options a shopper sees, decides whether a refund is instant or held, and tells the warehouse team which boxes need a closer look when they arrive.
Before shipping
Score orders so VIPs get a better return experience, abusers are flagged or limited, and bracketed orders trigger sizing outreach.
At return
High-risk returns get friction. Trusted customers get instant refunds.
At the warehouse
Parcels from suspected wardrobers go to a separate inspection.
Promo abuse
Linked accounts are blocked and stacked discounts cancelled automatically.
The takeaway
Brand details are anonymized. Figures come from the brand’s own order and return data.
Industry
Apparel
Size
$50M to $100M online sales
Platform
Shopify
Solutions
Return Abuse
Lookback
Historical orders and returns
At a glance
~10%
Return rate by value
~$140
Average order value
~500K
Orders a year
50%
Of returners returned more than one order
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Free lookback · for qualified brands
See what you lost last year. Free.
01
Share 12 months of data.
Install the Shopify app or SFCC cartridge, or send order, return and claim exports.
02
Get your lookback in under two weeks.
What you lost to return and claims abuse, and who took it.
03
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Run it on live orders, then decide.