Viral Returns Abuse: Social Media Highlights Need for New Strategies

Retail returns abuse has become internet famous. In recent months, social media users have populated posts on channels like TikTok, highlighting how they could save hundreds of dollars by taking advantage of returns policies set by retailers like Costco, Amazon.com, and Target. In fact, the videos have grown to become a veritable theme on social media, including “how-to” videos on ways to exploit retailer returns.

This isn’t entirely new behavior. Organized retail crime (ORC) rings already utilize dark web channels like Telegram to disseminate schemes and tips on how to defraud a retailer, such as how to use artificial intelligence tools to create fake receipts for returns. However, these influencer videos are public posts that, if spread far enough, can cut deeply into a retailer’s profits.

To contain the viral behavior, retailers don’t need to tear apart their current returns policies, as making a stricter policy could harm loyal customers. Instead, retailers can implement AI modeling into the returns experience that supports good customers while also catching bad actors.

Examples of Viral Abuse

Incidents of returns fraud and abuse are growing. Analyzing transaction data from 60 of the top 100 retailers and surveying 150 North American retail executives, research shows that retailers lost $103 billion to fraudulent and abusive returns in 2024. What’s more, this fraud and abuse represented more than 15 percent of total returns for the year.

Perhaps driving even more retail returns abuse are how consumers and influencers are sharing their tricks over social media. On the viral spectrum, recent examples include:

• TikTokers shared how they bought Cat & Jack children’s clothes, a popular private-label brand from Target, used the items, and returned them nearly a year later for more than $500.
• Costco shoppers flooded social media, creating almost a viral video challenge, demonstrating how they tested the limits of Costco’s returns policy by returning used and even damaged items.
• Amazon shoppers have been commonly sharing how they take advantage of the retailer’s returns policy on social channels.

These patterns of abuse and fraud join many tactics that retailers have been facing for decades. Common tactics of abuse include wardrobing (buying an item with the intention of using it temporarily and returning for a refund), bracketing (buying many variations of a product to test with the intention to return some or all the items), and false claims (filing a phony claim that a purchased item was never delivered or came damaged).

Returns Fraud Contained

As retailers eye ways to limit viral returns abuse, embedding AI models into return authorization systems can help catch suspicious behaviors in-store and online.

For instance, as a returns transaction comes to a retailer, AI can analyze that customer’s shopping history anonymously. Perhaps the shopper recently returned a mountain of kids’ clothing they bought for back-to-school shopping season, much like the Target example above. AI can flag that unusual behavior and recommend to an associate whether a return should be denied or investigated.

Retailers can leverage AI as a way to help associates personalize each transaction, rewarding loyal shoppers, while catching abusers. Retail data flowing to one centralized place, where AI can read shopper data and more, helps to deliver unbiased and customized recommendations on how each return should be handled. With AI, retailers can remove strict, blanket policies that upset loyal customers. Instead, AI preserves the integrity of a returns policy and limits the impacts caused by shameful social media grabs.

Libby Cooper is director of customer success at Appriss Retail, a company that reduces losses from retail fraud and theft while protecting the retail customer experience.