Holiday return abuse starts long before Black Friday and doesn’t always look like abuse. Say a regular customer reaches out to a brand through the chatbot on its website. She lets them know that she never received the shoes she ordered. The customer service representative apologizes for the inconvenience and refunds her $200, no problem.
The customer is happy and so is the brand, knowing that her satisfaction will likely result in another purchase. Everyone wins.
Except not really. The customer received the shoes, which she plans to resell at a markup. She also received the other pairs of shoes she claimed not to have received under different identities. Those will be resold, too.
While people file false Item Not Received (INR) claims all the time, wardrobing and reseller fraud, two of the most common forms of holiday return abuse, spike every year. With Black Friday and Cyber Monday just a few weeks away, merchants must understand who’s behind every return and set their holiday policies accordingly.
How holiday return abuse and reseller fraud impact the customer lifecycle
The term “abuse” casts a wide shadow across the entire customer lifecycle.
Reseller fraud starts with customers adding a high volume of items to their carts. They intend to resell their purchases at a markup, exhausting inventory and hurting the customer experience for legitimate shoppers.
At the point of sale, reshippers use different addresses to bypass purchasing restrictions. Promo abusers take advantage of discounts and rewards they’re not entitled to.
Post-purchase, holiday return abuse takes several forms. Customers return items they’ve used, a practice known as wardrobing, or intentionally send back the wrong item. Other customers don’t return anything at all, instead choosing to keep the item and the money. Forter data shows that false INR claims are up 30% year-over-year.
Understanding the buyer behind the behavior
Abuse is able to fester in part because without one true “owner,” its costs are widespread throughout the organization. The inventory, shipping fees, and margin hits from refunding fraudulent transactions are obvious. Below the surface, there are also the labor costs. Warehouse workers pack the orders that the customer service teams end up refunding for abusers.
A single order or account looks fine in isolation. Order-by-order controls miss cases of abuse.
Merchants can’t solve the abuse problem without identity.
Customer service representatives typically aren’t trained to identify fraud. If a customer’s profile doesn’t include refund data, the fraud team may not be aware of serial abusers. Some customers are also genuine victims of package theft, so not every INR claim is abuse.
You need a full picture of who a customer is beyond their transaction history. That includes thousands of first-party signals across devices, sessions, accounts, and behaviors.
With that single view of the customer — across many brands, not just your own — you can create the most effective policies that target abusers without penalizing everyone else. Blanket return fees, for example, have reduced return rates, but also driven customer churn.
When policy is powered by identity, you can give frictionless returns to trusted customers with no history of abusive behavior. You can also manually review cases for customers in the gray area, those who have abused policies without going as far as committing fraud.
How to curb return abuse during the holidays
Here are seven principles to apply before, during, and after the peak shopping season:
- Set rules and test them before the peak. Define purchase limits for hot items, return and INR policies, and promo rules. Test them before going live where possible, then publish them for customers.
- Look across identities, not just orders. Abusers split activity across accounts to get around single-order rules. Apply limits to the person, rather than the account, email, or card.
- Match the response to the risk. Decline clear abuse, and flag borderline cases for review. Don’t treat every reseller or high-volume buyer as abusive.
- Give good customers a way out. Provide a clear path to support and fast review for anyone wrongly blocked.
- Think beyond the sale. Returns and INR abuse only show up post-purchase, so track both through the holiday window.
- Measure both sides. Track abuse and leakage (revenue lost to abuse) alongside conversion, complaints, and repeat purchases.
- Review after the peak. Keep what worked and fix what blocked good customers. Apply it to January returns and the next product launches.
How Forter can help prevent holiday return abuse
Forter connects activity across accounts, devices, and brands to identify the individual behind every order and return with AI-driven, real-time transaction decisioning. Our network is built on a proprietary identity database of roughly 2 billion identities and more than 6,000 signals.
That lets us recognize a buyer as trustworthy across every merchant in our network, rather than relying on one merchant’s history alone. In turn, you can apply limits to the person rather than the account, approve trusted customers instantly, and route gray-area cases to review. Good customers who get caught can be reinstated quickly.
