Perspective: Understanding the Total Cost of Retail Returns
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The returns process is costly — and it impacts more than just profit margin. When factoring in every step a retailer goes through to ship, return and reship items, each transaction influences a retailer’s time, money and product waste.
Financially, retail returns totaled $685 billion in merchandise returned in 2024, from 60 of the top 100 U.S. retailers. What’s more, online returns — buy online, return in-store, and buy online, return online — combined for more than half of all returns. This trend matters because online returns burden how retailers impact the global carbon footprint.
Case in point: In 2022, the reverse logistics process produced 24 million metric tons of CO2 emissions and added 9.5 billion pounds of merchandise to landfills, according to Optoro. Also, retailers must continually train staff on returns processes — an effort that consumes time and resources.
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These factors are only part of the cost of returns, which also include:
- Warehouse and storage expenses
- Transportation fees for returns shipping
- Labor costs for processing and customer service
- Inventory losses and refurbishing efforts
- Administrative overhead managing returns systems
While returns are complex and expensive, AI can help retailers streamline operations and reduce financial losses.
(Optoro 2022 Impact Report)
Pains of Returns — Fraud and Theft
Retailers and loss prevention teams tend to leverage technology like AI to reduce fraudulent return incidents, claims abuse and outright theft. It’s important, as organized retail crime (ORC) groups are becoming savvier, finding ways to work around online systems to steal products. Sadly, some consumers also abuse returns in common ways.
One leading tactic is “wardrobing” (or “renting”), which is when a consumer buys an item with the intention of using it once and returning the product for a refund. Another is “bracketing,” or buying many products to sample and return most — or all — of the items. The former tactic affects 60% of retailers, .
Yet, while retailers seek ways to slow down fraud and abuse, there’s more retailers can learn about their returns process by deploying AI and retail analytics. AI can improve overall operations by reducing the time associates spend handling returns and providing insights into why items are frequently returned. For instance, a housewares retailer can receive a report flagging that a candle continues to be returned due to the product breaking during shipment. The company can revisit the candle’s packaging to strengthen it, reducing the number of times it gets returned.
How AI Improves Returns
To start, it’s important for retailers to establish a streamlined and centralized method of harnessing data throughout the organization. Optimizing retail returns starts with giving all parts of an organization visibility into where returns are being processed — online, in-store and call centers, for example.
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AI helps retailers by analyzing return data across all channels in real time. It anonymously reviews a shopper’s purchase and return history, looking for patterns — like frequent returns and multiple identities, addresses or payment methods. Using this data, AI-powered return authorization systems can instantly recommend whether to approve or decline a return.
Outside the point of return, teams can further leverage retail analytics to monitor incidents of fraud and abuse, enabling generative AI capabilities to connect cases that could lead to ORC syndicates. AI analysis can also scan transaction data and history to flag issues in transaction data — like recurring returns of the same product or unusual return patterns tied to specific employees — helping retailers take targeted, informed action.
Returns Refined: Save Time, Money and Sustainability
AI and retail analytics provide retailers with an omnichannel view of their returns, identifying root causes of why products are getting sent back or if there are cases of abuse and fraud. Every return is unique, and retailers need AI to help keep an eye on how each transaction is being processed, the behaviors and history of the shopper returning an item and how that return impacts the company overall.
oversees ’s customer growth and retention departments, including sales, customer success and marketing.
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