Send-Back Season: Managing returns post-summer deal days

It’s been 10 years since Amazon launched its first Prime Day event, running the massive sales promotion for 24 hours on July 15, 2015. 

Since then, the event has expanded to include multiple days and reach more countries. At the same time, Walmart, Target, Dick’s Sporting Goods, and other retailers began to host their own competing deal days in the summer. And just like that, a new season was created — Black Friday in July.

Retailers have long run promotions in July, timing them around the Fourth of July and using them to kick off back-to-school shopping, but Prime Day was designed to go further. Consumers save on items across every aisle, touching more than 35 categories, and jumping on savings as high as half off on electronics. Like Black Friday, the slashings power a slew of impulse buys, and, unfortunately, it can lead to a spike in returns in August.

Appriss Retail research uncovered a 10-15% increase in returns happen after summer deal days. Consumers with itchy shopping fingers can purchase items at steep discounts on a whim and later realize they no longer want the product. There also could be an uptick in abusive and fraudulent behavior during the increase in deal days returns.

Deal days spark more year-over-year sales

The new summer sales season, or Black Friday in July, is likely here to stay, as seen by some of the results of this year’s performance, including:

• Walmart+ Week shoppers spent 11% more per basket than last year.
• Amazon’s Prime Day 2025 broke sales records, in part because the event expanded to
  four days for the first time.
• Over one-third of consumers compared offerings across multiple retailers before making their final purchase, leading to $24.1 billion in online sales.
• Retailers are clearly seeing the benefits of a summer sales event, but to get the most out of it, they need to have a returns strategy in place that reduces returns and keeps consumers loyal.

An optimal returns strategy prepares them for these significant returns increases.

AI helps retailers secure summer profits

With an increase in orders, naturally, a retailer may see a spike in returns and in fraud and abuse. For instance, during high-promotion periods and urgent seasons like back-to-school, consumers are prone to dabble in some harmful behaviors such as:

• Wardrobing — Or buying an item to use it once, only to return it quickly afterward, never intending to keep it.
• Bracketing — An act of purchasing variations or styles of the same product to sample at home, expecting to return most or all of the items.
• False claims — A deceitful act of buying an item and then fraudulently filing a claim that the item never arrived or that it appeared damaged, requesting a refund or reward in return.

Because deal days only run for a few days, accelerating a rush on orders, bad actors like to try these abusive shopping behaviors, thinking retail associates will be overwhelmed. No doubt, they are, but retailers with AI built into a strategy can help keep watch.

AI can assist retail teams by analyzing data from online and in-store returns as they occur. At the point of the return, the technology anonymously reviews a shopper’s purchase and return history, looking for odd behaviors like frequent returns history and multiple addresses or payment methods assigned to a purchase. Then, with this behavioral data, AI provides a recommendation to an associate on whether a return should be approved, declined, or flagged for concern. The technology supports retail team members to become more efficient about managing returns during this flash flood of orders and subsequent returns, ensuring only the items meant to be returned get a refund.

Stringent returns policies turn off deal days shoppers

Another benefit of using AI within a returns strategy is that it can enable retailers to treat each return transaction uniquely. Too often, as part of a major deals event, retailers rewrite the returns rules, saying all items can’t be refunded, for example.

These sudden strict returns policies can upset consumers. Instead, with AI, retailers can identify consumers who have a long history of shopping and who have been spending a lot of money. Ultimately, they can keep those central consumers happy by honoring their returns during these events. At the same time, the technology helps identify fraudulent and abusive returns and manages those consumers appropriately.

With retail analytics and AI, retailers can ensure they generate peak sales during the summer and be prepared for Send-Back Season.