Online returns used to be treated as a cost of doing business.
For years, generous return windows, free postage and easy refunds helped remove friction from online shopping. They gave customers the confidence to buy fashion, footwear, homeware and lifestyle products without seeing or trying them first.
But over the past 24 months, the economics have changed.
Returns are no longer a small operational inconvenience. They have become a margin problem, a customer experience problem, a fraud problem and, increasingly, a strategic problem for online retailers.
Why returns have become such an issue
Consumer behaviour has shifted.
Online shoppers have become more comfortable using returns as part of the buying journey. Ordering three sizes and keeping one. Buying multiple colours to choose at home. Purchasing for a specific event and sending the item back afterwards. Using buy-now-pay-later to place larger baskets, knowing some of the order will be returned.
For many customers, the basket is no longer the final purchase decision. It is the start of the selection process.
That creates a major issue for retailers.
A sale is not really a sale until the return window has closed. Stock that appears sold may be unavailable for weeks, only to come back damaged, creased, out of season or harder to resell. The retailer carries the cost of fulfilment twice: once to send the product out, and again to bring it back.
At the same time, retailers are dealing with higher carrier costs, wage inflation, discount-heavy trading and customers who remain highly price-sensitive. That means returns are now much harder to absorb.
Every returned item carries a chain of costs: picking, packing, dispatch, return postage, inspection, repackaging, refund processing, customer service and potential markdown.
In categories like fashion, the margin impact can be brutal.
Customers still expect convenience
The difficult part is that retailers cannot simply make returns painful and expect the problem to disappear.
Customers now compare returns experiences in the same way they compare delivery, price and reviews. A poor returns policy can stop a purchase before it happens. A slow refund can damage trust. A confusing process can push customers to a competitor.
That leaves retailers with a balancing act.
Make returns too generous and the business absorbs rising costs. Make them too restrictive and conversion suffers. The challenge is to protect the customer experience without letting returns quietly destroy profitability.
Retailers are starting to change the rules
One of the most visible changes has been the move away from blanket free returns.
Zara now charges for some UK drop-off returns while still offering free in-store returns. H&M has also introduced return fees in some markets, while keeping returns free for loyalty members.
This is not just about recovering postage. It is about changing behaviour.
A small fee can reduce low-intent ordering and encourage customers to think more carefully before placing large speculative orders. Free in-store returns can also push customers back into shops, where stock can be checked faster and the retailer has another chance to make a sale.
ASOS has also been open about reducing avoidable returns and improving profitability. Its approach shows where the market is heading: returns are now being managed as part of trading performance, not just as a customer service issue.
The best return is the one that never happens
A lot of returns are created before the customer ever receives the parcel.
Poor sizing information, weak product descriptions, misleading photography, inconsistent fit, missing dimensions and limited customer reviews all increase uncertainty. If the customer has to guess, the retailer increases the risk of a return.
That is why better product content is one of the most effective ways to reduce return rates.
Retailers need clearer size guides, better imagery, model measurements, fit notes, customer reviews and more useful product data. For fashion, this might mean “true to size” guidance. For homeware, it may mean better dimensions and lifestyle photography. For beauty, it may mean shade-matching tools and clearer suitability information.
The goal is simple: help the customer buy the right product first time.
Turning refunds into exchanges
Retailers are also trying to stop every return becoming a lost sale.
Platforms such as Loop Returns, ZigZag and Happy Returns help retailers turn returns from a basic refund process into a more managed customer journey.
Instead of defaulting to a refund, the returns flow can encourage exchanges, store credit or alternative products.
For example, BullyBillows used Loop Returns to support exchanges and apply different rules when customers choose refunds. Oh Polly has also worked with Loop to improve exchanges, store credit and customer retention.
The commercial logic is clear. If a retailer can convert even a small percentage of refunds into exchanges, it protects revenue and keeps the customer relationship alive.
Using stores as return hubs
For omnichannel retailers, stores are becoming an important part of the returns strategy.
In-store returns are often cheaper, faster and more controllable than postal returns. They also bring customers back into a retail environment.
New Look has used ZigZag return kiosks to make in-store returns easier, using QR codes and self-service flows to reduce friction for customers and staff.
Happy Returns has built much of its proposition around physical drop-off points and return bars, helping retailers reduce reliance on traditional mail returns and speed up processing.
For pureplay retailers, this is harder. They need partnerships with lockers, convenience stores, drop-off networks or third-party return locations. But the principle is the same: the faster an item is inspected and returned to sale, the less value is lost.
Returns data should drive better decisions
One of the biggest missed opportunities is returns data.
Many retailers know that something was returned, but not enough about why. That data should be feeding back into product, merchandising, buying, content and customer service.
If a product is repeatedly returned because it is “too small”, the issue may be sizing or fit guidance. If customers say an item “doesn’t look like the picture”, the issue may be photography. If return rates spike on one supplier’s products, there may be a quality issue.
Retailers such as SportsShoes and ECCO have used ZigZag reporting to better understand sizing issues, faulty items and return reason patterns.
Narvar’s work with Signature Hardware also shows how better returns visibility can reduce customer service queries and give retailers clearer insight into what is being returned and why.
Returns should not just be seen as a refund workflow. They should be treated as customer feedback at scale.
Tackling fraud and serial return behaviour
Not all returns are equal.
A genuine customer returning the wrong size is very different from someone repeatedly wearing items and sending them back, switching products, making false damage claims or abusing refund policies.
Retailers are now using better data to identify high-risk patterns without making the experience worse for everyone.
That might include flagging customers with unusually high return rates, repeated claims, frequent returns of high-value items or behaviour that suggests wardrobing.
Happy Returns has highlighted how in-person drop-offs and item verification can help reduce return fraud. This is where smarter rules, inspection processes and customer-level decisioning can make a real difference.
The key is fairness. Good customers should not be punished because a small percentage of shoppers abuse the system.
What retailers should do now
The answer is not simply to start charging for every return.
Retailers need to understand the shape of the problem first.
That means measuring return rates by product, category, size, customer type, channel and reason. It means understanding the cost of each return route. It means knowing how many refunds could become exchanges, how quickly stock gets back into sale, and where returns are damaging the margin most.
From there, retailers can act.
They can improve product content, introduce better size guidance, encourage exchanges, offer store credit, use stores as return hubs, apply fairer return policies, identify fraud earlier and connect returns data back into buying and merchandising decisions.
Technology can help, but only when the operating model is clear.
AI can support return prediction, fraud detection, size recommendations, product matching and customer segmentation. Automation can speed up refunds, route stock more intelligently and reduce manual customer service work.
But the real shift is strategic.
Returns are no longer just the bit that happens after the sale. They are part of the sale.
The retailers that handle this best will not simply make returns harder. They will make them smarter.
They will protect good customers, reduce avoidable returns, retain more revenue, process stock faster and give the business a clearer view of true profitability.
In online retail, growth that disappears through the returns process is not really growth at all.
