Amazon Prime Day is expected to generate a large wave of returns in the UK, with Manhattan Associates research estimating that 61 million items could be sent back after this year’s event.
The study suggests nearly half of items bought during Prime Day could be returned, equal to 47% of purchases. It estimates that 65% of UK shoppers will buy during major discount events, purchasing an average of 2.39 items each, with the total volume of Prime Day purchases expected to reach 131 million items.
Prime Day is running from 23 to 26 June this year, making the event longer and more operationally demanding than a single day promotion. The returns forecast points to the hidden cost of high volume discount retail: every order placed during a sales surge can create follow-on pressure across reverse logistics, refunds, stock handling, customer service, and fraud controls.
Keith Dipple, EMEA unified commerce sales director at Manhattan Associates, said Prime Day “puts the entire commerce operation under enormous strain.”
The demographic data adds another layer. Shoppers aged 25 to 34 are expected to be among the most active, while 36% of consumers now use AI to inform purchase decisions. Manhattan Associates estimates that as many as 47 million Prime Day purchases could be AI influenced this year.
That behaviour affects the shape of demand. AI-supported shopping can increase product discovery and comparison, but it may also encourage faster, less certain purchasing. When shoppers use AI tools to identify bargains, compare specifications, or shortlist alternatives, retailers need product information, fulfilment promises, sizing data, and returns policies to be accurate across the buying journey.
Returns are no longer a postscript to ecommerce. They are a core operating cost. Items come back in different conditions, through different channels, at different speeds, and with different customer expectations. Some can be resold quickly. Others need inspection, repackaging, repair, markdown, disposal, supplier return, or fraud review. The speed and accuracy of those decisions affect margin.
The economics can be punishing. Free or low cost returns have helped grow online retail by reducing customer hesitation, but they also transfer risk back onto retailers and marketplaces. Delivery, processing, customer service, warehouse labour, payment fees, and inventory depreciation can erode the profitability of discounted orders. During promotional events, the scale magnifies the problem.
Retailers are already wrestling with how to turn AI ambition into measurable value, as explored in Retailers face AI strategy gap. The Prime Day returns forecast shows another side of the same challenge: AI may influence demand, but commerce systems also need to handle what happens after purchase.
The challenge stretches across the sector, not only Amazon. Prime Day sets customer expectations for price, speed, and convenience, forcing other retailers to respond with their own promotions, delivery promises, and return policies. That can create a market wide spike in volumes at the same time that warehouse labour, courier capacity, and customer service teams are under pressure.
Retailers may need to rethink how they measure promotional success. Gross sales, order volume, conversion rate, and basket value can look strong during a discount event, but the final economics depend on retained purchases. A campaign that generates high sales and high returns may leave little margin after reverse logistics costs. Returns adjusted profit is becoming a more useful measure than headline demand.
Product data is part of the answer. Better sizing information, richer images, clearer specifications, customer reviews, fit tools, and accurate delivery promises can reduce preventable returns. So can better segmentation, where retailers identify customers or categories with unusually high return rates and adjust policy, pricing, or communications accordingly.
Technology also has a role in the warehouse. Returns management systems, inventory visibility, automated grading, refund rules, resale routing, and fraud detection can help companies recover value faster. The most advanced operators treat returns as a flow of stock and data, not a pile of exceptions.
The customer experience risk remains delicate. Tougher return policies may protect margin but can weaken trust, especially in fashion, electronics, and categories where uncertainty is common. Lenient policies can encourage purchase, but they may also train customers to over-order. The strongest retailers will be those that make buying more accurate before tightening the returns process.
Prime Day remains one of the largest retail demand events of the year. The estimated 61 million returns show that its operational impact continues long after checkout. The winners will be judged not only by how much they sell, but by how much value they retain after the parcels come back.
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