The 2025 holiday season delivered the first trillion-dollar holiday in U.S. retail history, with online spending alone hitting $257.8 billion. But while the sales numbers made headlines, the returns story was more complicated.
According to Adobe Analytics, returns were actually down 1.2% compared to last year during the core November to December shopping window. Then came the flood: returns surged 4.7% in the days immediately following Christmas, with volumes spiking at 25% to 35% leading up to the new year.
That pattern of a brief reprieve, followed by an intense post-holiday wave, put a spotlight on what’s really driving return costs: fraud, abuse and the operational strain of handling millions of items in a compressed window.
In a year when operating margins are already thin, these behaviors are turning what used to be a customer service cost into a serious financial risk. Here’s how merchants are preparing for that collision — all without alienating loyal shoppers.
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What Happened During the 2025 Holiday Season
Data from the National Retail Federation estimated that retailers would process $849.9 billion in total returns during 2025, with online return rates hovering near 19.3%. Returns used to reflect uncertainty about a product; now they reflect uncertainty about spending power. Shoppers have begun using them to manage budgets, delay commitment or stretch cash flow through “buy now, return later” behavior.
And as consumers push for flexibility, opportunists are following close behind. For every legitimate return, others exploit refund loopholes, manipulate automation gaps or abuse lenient policies designed for loyalty rather than loss prevention.
Against that backdrop, the stakes in 2026 are higher than ever.
The Post-Christmas Surge
The shift toward early holiday promotions, starting as soon as October, meant return cycles opened before peak shipping weeks. Retailers faced a 10- to 12-week return horizon, up from the traditional four to six weeks, complicating inventory forecasting and resale timing well into February. And while return rates held steady during the shopping rush, the post-Christmas spike hit hard, Adobe predicted elevated levels through mid-January.
Certain Categories Bore the Brunt
Apparel remained the leader in returns, where “bracketing” (ordering multiple sizes or colors with the intent to send most back) has become a normalized shopping behavior — nearly two-thirds of online shoppers engage in this practice. For some fast-fashion retailers, return rates topped 30%, with a growing share of those tied to “wear once” or wardrobing behavior.
A Spike in “Friendly Fraud”
“Friendly fraud” (including false damage claims, “item not received” disputes and serial refunds) now represents roughly 15% of all return-related losses, costing retailers over $100 billion annually. Each fraudulent claim chips away at already-tight margins and forces retailers to choose between protecting profits and preserving goodwill.
Rising Cost per Return
The average cost of processing a return now exceeds $27 for a $100 order, once restocking, shipping and inspection labor are factored in. For low-margin products, that can wipe out profits, even when the merchandise is resold.
Omnichannel Blind Spots
The convenience of buying online and returning in-store has blurred oversight. Without unified systems, fraud teams may not see cross-channel return patterns, like the same customer returning items purchased under different accounts or payment methods.
What Retail Leaders are Doing Differently in 2026
Retailers know they can’t simply tighten the screws without risking loyalty. The very policies that create trust — fast refunds, no-questions-asked exchanges, extended return windows — have become a balancing act between generosity and control.
Instead of tightening policies across the board, leading retailers layered automation, data and behavioral insight to make every return decision dynamic.
Automating Trust Decisions
AI-powered verification tools can cross-check orders, payments and tracking data before a refund is issued. By flagging inconsistencies, such as repeated “item not received” claims or mismatched return weights, they help reduce the burden on overwhelmed support teams while preventing false refunds.
One brand using NoFraud managed to block nearly $50,000 in monthly losses from fake tracking IDs and shipping manipulation alone. And across multiple retailers, automated verification now identifies and declines roughly 5% of claims driven by fraud or abuse while speeding up resolution times for legitimate customers.
Unifying Chargeback, Order and Return Data
Some retailers are consolidating fraud, logistics and customer service into unified risk engines. This allows for pattern recognition across millions of transactions — spotting, for example, a customer who returns the same SKU across multiple accounts or who consistently disputes high-value orders.
Segmenting Risk, not Customers
Some sellers are applying fraud scoring to return requests in real time. Shoppers with a strong purchase history receive instant approvals or pre-paid labels; meanwhile, high-risk profiles trigger a brief manual review. This results in legitimate customers enjoying frictionless service while abusers encounter invisible guardrails.
Personalizing Return Policies with AI
Retailers are beginning to customize the return rules themselves by tailoring window lengths, restocking fees and refund timing based on a shopper’s behavior and product category. A loyal customer might receive instant store credit or a 60-day window, while repeat abusers might see shorter timelines or credit-only options. By replacing one-size-fits-all policies with data-driven flexibility, merchants can reward good behavior without exposing themselves to risk.
Building Empathy into Automation
Returns are often the most emotional moment in the customer journey. The most effective AI systems can route each case to the right resolution channel. Low-value items may be marked as “keep it” to avoid shipping costs, while high-value returns get handled by live agents who can recover trust in real time.
Connecting Insights Back to Merchandising and Marketing
Leading brands are feeding return data into product and content teams. If an item has a 35% return rate for “fit,” marketing might adjust its imagery or descriptions; if a category drives high abuse, it might prompt a re-evaluation of pricing or packaging.
Returns will always be part of retail, but in 2026, they’re also becoming a mirror for how each brand manages trust. Instead of trying to eliminate returns, shift your mindset to see them as a recurring investment in customer lifetime value. The sellers that succeed won’t be the ones with the strictest policies, but the ones that turn these signals into smarter operational decisions.
Scott Gifis is the CEO of NoFraud. With more than 20 years of leadership experience, he previously served as President and COO of Frame.io, acquired by Adobe for $1.3 billion, and as President of AdRoll. Gifis also has held executive roles at OpinionLab (acquired by Verint Systems), Criteo, CareerBuilder and TeraSolar (which was sold in 2005).
