Customer returns represent a long-standing complication for retailers, but with the continued rise of online shopping, the problem has grown both in size and in cost: According to an Appriss Retail report, in 2017, retailers lost out on more than $351 billion in sales due to merchandise returns.
Though reducing that impact is no easy task, emerging technologies such as artificial intelligence, data analytics and mobile applications give retailers a fighting chance.
AI Takes the Guesswork Out of Online Shopping
While some customers will always be of the “buy many, keep one” mindset, others prefer a more straightforward shopping experience — one that doesn’t end in a return. AI-powered personalization tools help that latter group purchase the right products the first time around.
Cloud-based True Fit technology, for instance, relies on a brief customer survey and an extensive database of product data to offer shoppers personalized size, fit and style recommendations.
“It makes people more confident in making their purchases,” says Brian Seewald, vice president of digital at shoe retailer DSW.
DSW, along with Macy’s, Nordstrom and other major brands partnering with True Fit, can see tangible results from the data-driven intelligence platform.
“Consumers who use True Fit buy more and return less,” according to a company press release, which notes that the technology generally contributes to a 3 to 7 percent incremental sitewide lift in net revenue.
Data Gives Retailers Visibility into What Went Wrong
Beyond fit and sizing issues, quality issues, unmet expectations and shipping errors often contribute to high return rates. Sometimes, the key to reducing these returns is as simple as updating product descriptions for clarity and accuracy; but that can only happen if retailers have access to the right data and tools.
Advanced solutions such as the Qlik analytics platform give retailers deep visibility into sales, returns and customer data across all channels — including mobile applications and call centers — to deliver actionable insights.
“When retailers can quickly identify trending issues with the products they sell through collecting and analyzing returns data, they can make smart decisions like knowing when to encourage returns, and how to change products and processes to please customers,” writes Peter Sobotta on the ReturnLogic blog.
Mobile Applications Further Simplify the Returns Process
According to a 2017 UPS survey, 66 percent of customers who returned an item in-store then went on to make a new purchase. By comparison, only 44 percent of shoppers who shipped back a return made a new online purchase. Those incremental sales mean brick-and-mortar retailers can gain an edge over online-only competitors by offering buy online, return in store programs.
“But these types of programs create an expectation on the part of customers that their experience of switching between website and store will be seamless,” writes CDW insights manager Lisa Wood.
Walmart’s Mobile Express Returns program, which launched in late 2017, demonstrates how effectively mobile applications can bridge the divide between online and in-store channels. The brand’s time-saving program enables customers to initiate their returns via mobile and then fast-track through the returns line once they arrive in a store. Associates only have to scan a QR code displayed in the customer’s app to complete the return.
“We’re changing the returns game in ways that only Walmart can do,” says Daniel Eckert, senior vice president of Walmart services and digital acceleration for Walmart U.S.