Returns cost retailers $706billion in 2025, and nearly tripled after Christmas, making brands reconsider how they approach returns and total retail loss together, says Shaun Callow, Senior Customer Success Manager at Appriss Retail.

Returns represent the vast majority of money lost inside a retailer’s business, yet much is preventable. Transaction data from Appriss Retail’s enterprise retailer clients showed that in 2025 retailers saw $796billion lost due to returns and shrink. Of that number, $706billion can be attributed to returns, with $100 billion coming from returns fraud and abuse.

Retailers leveraging AI tools across channels – in-store, online and customer service call centres – can reduce loss in returns fraud and abuse. For example, AI-driven analysis can spot suspicious returns patterns, as well as review a shopper’s returns history for abusive behaviours leading to less loss. The technology, when working across channels, also helps organisations address total retail loss beyond returns, spotting key areas of shrink, such as inventory and operational errors.

To grow profit margins, retailers must look deep at where they can regain loss – and it starts with returns.

Golden Quarter returns peaks

From early October through Christmas and Boxing Day in the UK, brands and retailers operate at a fever pitch to move units and make sales. And then comes the other side of the frenzy: returns.

So how much are retailers losing after Peak Trading? Our data, which studied 250million unique customer identifiers across enterprise retailers, explored how returns impacted businesses – this showed return rates nearly tripled after Christmas (16%) compared to July (6%). The comparison is significant, as many retailers host summer sales events in July that spark returns.

But the data shows there’s nothing like the festive returns season; return rates peaked at nearly 19% on 29 Dec and stayed elevated above 13.5% every day after New Years Day.

Considering UK shoppers broke online sales records during this year’s Peak Trading season, returns could be expect to be high – but the losses remain a problem as retailers fight dwindling profit margins and rising revenue goals.

Align returns with total retail loss

It’s true that returns are a leading cause of financial loss for retailers, with returns fraud and abuse accounting for 20% of shrink. Add in the frictional costs caused by returns, such as reshipping items and repackaging them for resale, and the losses pile up quickly.

Yet, returns are also only one part of the total loss picture. The other 80% of losses come from non-fraud sources that often go unnoticed, such as damaged goods, food waste, process breakdowns and supply chain inefficiencies.

For retailers to improve how they reduce returns, the first step is to build a company culture that views returns as part of a total loss problem. This requires executives at the highest level of the company to bring together loss prevention (LP), asset protection (AP), IT, supply chain, and all facets of the company to review loss holistically.

The goal is to eliminate silos and bring LP and AP teams to the table. By doing so, having all teams unified and working from the same data, returns can be better understood and addressed.

Get proactive to reduce returns

Once retailers change culturally to accept returns, shrink and total loss as a connected problem, there are also technology considerations. Just as company leaders get aligned around returns and loss, omnichannel transaction data, returns data and more must be centralised and made available across teams.

From C-level executives to managers, unified data and AI-driven analytics help retailers identify loss as it’s happening. From a returns perspective, AI can analyse data and turn it into actionable intelligence to spot potential fraud and abuse.

For the post-Christmas rush on returns, this is essential. For each return during the busy period, AI can analyse transaction data, shopper behaviour histories and loyalty information to provide a recommendation on whether a return should be accepted, denied or simply warn a consumer of a potential abusive behaviour.

As a result, AI tools can catch abuse or potential fraud right then and there to limit loss, while preserving the customer experience.

More broadly, having returns data and more in a centralised place enables teams to study larger patterns happening with returns. Perhaps a homeware retailer uses AI to study the data and finds a rise in returns regionally on one lamp. After digging into the returns pattern further, the retailer could discover that the lamp has been breaking during shipping. This finding could push the retailer to revisit how it’s shipping from that warehouse and make necessary changes to avoid further damages.

The key for retailers is to be proactive to improve returns and protect against further profit loss.

Protect profits against rising returns

Our data show returns are increasing – just as retailers fight to maintain thinning profit margins. By implementing a more connected culture around returns and loss overall, and utilising AI-powered analytics, retailers can halt leaking profits as they’re happening.

Returns fraud and abuse are a leading driver of total loss, but they also represent opportunities for retailers to lift their P&L without raising prices or slashing growth investments.

By embracing a data-driven strategy to address returns and total loss, retailers can see profit margins increase and maintain consumer loyalty.