Man sealing parcel with duct tape.
Retailers may have good reason for festive cheer this holiday season, as the average household spend for the season is $613, which is 4% higher than 2023, according to Accenture Annual Holiday Shopping Survey. While a festive boost to the bottom line will come as welcome news to retailers, there is one unfortunate side-effect that increased shopping for party outfits and gifts for loved ones brings to the mix, and that’s managing the surge in returns come January.
Merchandise returns cost retailers in the United States billions of dollars every year and are becoming an increasingly challenging problem—so much so that in 2024, the cost of returns is expected to hit $890 billion in 2024, according to a new report by the National Retail Federation and Happy Returns, a UPS company. Retailers estimate that 16.9% of their annual sales in 2024 will be returned.
A complex challenge with no quick fix
The returns challenge is multifaceted. Firstly, online shopping has made it easier than ever for consumers to buy multiple items with the intention of returning some. Additionally, economic uncertainty has made shoppers more cautious, leading to higher return rates as they seek the best deals.
This puts immense pressure on retailers’ logistics and warehouse operations. Then there’s the environmental impact of items that can’t be resold often ending up in landfills. There is also the careful balance to strike in preserving tight profit margins, while also maintaining customer loyalty and brand reputation.
To manage the growing glut of returns and their associated expenses — retailers are rethinking their strategies for managing returns. We have seen some introduce fees to discourage online returns, while others are telling customers to keep goods they want to return because processing, repackaging, and reselling are too costly. They will refund you without needing the items back. Then there’s incentives to exchange — rather than return — a product, improving warehouse restocking processes and offering unique perks to frequent customers that shop at full price.
Prevention through improved information
Another way retailers can reduce returns is to improve product descriptions and overall quality of the information customers are using to help decide on what to buy.
Accenture’s Annual Holiday Shopping Survey found that more than two-thirds of consumers could face “buyers’ block” — the effect of feeling overwhelmed by number of options to choose from. The result? The majority (82%) say they will abandon their shopping carts due to frustration or indecision, and nearly 33% will shop elsewhere.
This is where tapping into shopper data can help. Pistola, for instance, is analyzing return data to identify common issues such as sizing and fit. The Los Angeles-based womenswear brand founded, then takes this data to update product descriptions to include more detailed, or nuanced, information to help customers make a purchasing decision. For instance, advising customers to size down on a particular style of jeans can significantly reduce the return rate for that item.
Then there’s ensuring warehouse operations are running efficiently and effectively. Boden, a UK-based womenswear brand, has implemented a strategy of moving team members from packing new orders to processing returns during high-demand periods. This approach helps to speed up the restocking process and ensures that returned items are back on the shelves as quickly as possible.
Prevention through advanced technologies
There is an important role for technology to play in preventing returns. For example, retailers can also reinvent their returns operation by integrating technologies such as artificial intelligence (AI), mobile apps, advanced tracking systems, robotics and data analytics.
Then there’s virtual try-on and sizing tools, powered by generative AI (gen AI) and augmented reality (AR). Particularly useful in categories like apparel and cosmetics, where fit and color are critical factors, this technology allows customers to see how a product looks and fits before making a purchase and can significantly reduce the number of returns due to poor fit or mismatched colors as a result.
Generative AI (gen AI) can help reduce product returns by providing personalized recommendations to customers. Accenture’s survey found that the majority (81%) of shoppers wish they could make decisions on what to buy more quickly, easily and confidently, and 73% say they would welcome inspiration, retailers can differentiate and drive revenue through inspiring and guiding consumers at each stage of their shopping journey.
This is where gen AI can really help by suggesting products that better match customers’ needs and preferences, thereby reducing dissatisfaction and returns. One way it can help is through enhancing website descriptions to improve product quality and deliver personalized offers and deals in real time.
Another way it can help is through AI-driven customer service systems, such as intelligent chatbots and virtual assistants. These can guide customers toward the best purchasing decisions by providing instant responses to product-related questions, for example, “best coat for cold temperatures” or “a red dress for a party that costs less than $100 dollars”. This kind of capability helps to improve the accuracy of initial purchases and reduces the need for returns.
Reinventing the returns playbook
The challenge of managing returns this holiday season is a significant one for retailers. However, by adopting innovative strategies and leveraging technology, retailers can reduce return rates, improve customer satisfaction, and mitigate the environmental impact of returns. Whether it’s through improving product descriptions, streamlining warehouse operations, prioritizing customer loyalty, or using gen AI to enhance personalization, retailers have a range of tools at their disposal to address the returns challenge effectively.