AI and Returns Rules Put Retail Logistics Under Pressure
Retailers tightening returns controls could be putting customer loyalty at risk, according to Blue Yonder’s 2026 Consumer Retail Returns Survey. Among 1,001 UK respondents, 89% said they would shop less often or leave a retailer altogether if frequent returns led to limits on their ability to send products back.
The findings have direct implications for fulfilment and reverse-logistics operations. More than half of UK consumers, 52%, have chosen one retailer over another because of its returns policy, while 35% stopped shopping with a retailer after rules became stricter during the past year. Monthly returns are less common in the UK than in France or Germany: 25% of respondents return an item at least once a month, compared with 48% and 46% respectively.
Technology must distinguish cost from customer value
Retailers are increasingly using data and AI to identify frequent returners. UK shoppers are divided on the approach: 36% consider tracking a fair way to manage costs, but 22% see it as invasive and say it would send them elsewhere. The generational split is notable. If directly told that their returns were excessive and then restricted, 62% of Baby Boomers would stop shopping with the retailer, compared with 39% of Gen Z respondents.
For operators, the challenge is not simply setting a stricter threshold. Systems need to combine customer history, item economics and fulfilment costs so that policies reflect both fraud risk and long-term value. A low-value product may be cheaper to refund without requiring physical shipment, while a resaleable item may justify a conventional return route.
AI recommendations expose product-data weaknesses
AI-assisted shopping is adding complexity. Nearly one quarter of UK consumers, 23%, have bought an item after an AI recommendation; 41% of those shoppers returned such a purchase within the past year. The leading reasons were a mismatch with the description, cited by 37%, and incorrect size or fit, cited by 26%.
Only 17% of all UK respondents trust AI to recommend the correct size or fit, while 37% do not trust it at all. This suggests that recommendation engines cannot be separated from accurate, machine-readable product information. Poor attributes, descriptions or sizing data can translate directly into avoidable transport, inspection and repackaging work.
Consumers still prioritise free return shipping and rapid refunds. Nevertheless, 58% were told to keep an item rather than return it during the past year, and 67% of that group said the experience made them more likely to shop with the retailer again. Such “keep it” decisions can reduce handling and transport when the recovery value of an item is lower than processing costs. Environmental concerns may also influence the model: 56% worry about returned goods going to landfill.
