Returns are the new normal in retail. According to NRF, 34% of people in the US said they would return at least one gift they got this holiday season. Using that as a benchmark for the frequency of returns, there is a huge opportunity for retailers to utilize data to make the returns process easier for a better experience.
Merchandising and Planning
According to Statista, 75% of returned items were clothing and accessories. By capturing data to understand what was returned and why, a retailer may see if there is an issue with their sizing, color or quality of the product. The NY Post found that the most returned items last holiday were, “shirts with bell sleeves, fringed boots and tiny sunglasses.” This points to fashion trends being a driver of these returns, as certain pieces of clothing and footwear may have gone out of style in between the time of purchase and time of the return – or were simply poor gift choices. Collecting this type of data can be important to plan out future inventory, as well as potentially prevent returns in nearly real-time by updating product imagery or sizing recommendations on the PDP (product detail page) to help the customer make a better choice up front based on more accurate information.
What customers buy and return can also help indicate which products to market to them in the future. A study done by RedStag Fulfillment found that by understanding their return behaviors both online and off, retailers can more accurately target their customers with personalized communications, or “curation of products based on purchasing data.”
Seamless Returns Process
Retailers also need to ensure the returns process is seamless for the holidays. When customers are happier, it provides opportunities to build stronger connections to increase retention and upsell opportunities. According to our consumer research on returns, 95% of customers that are satisfied with the returns process would purchase from that retailer again.
Using data to inform the returns process illustrates what areas have friction and what aspects are succeeding in order to increase customer satisfaction. For example, having a better tracking and notification solution may make the difference between repeat customers or one-time transactions. In our Hierarchy of Needs study, 80% say that being proactively updated on delivery schedules, including information on delays, makes them more likely to purchase from that retailer again.
In addition to knowing which items are being returned and why, retailers can also use location data to optimize the returns process. AdWeek contends that location data can be used to identify the amount of returns to a certain store to predict store traffic during certain times. As a result, this helps prepare stores for additional staffing needs during the holidays to decrease wait times. In these instances, year-over-year (YOY) returns data ultimately provides stores the information to provide a better overall experience, establishing more personal relationships with customers.
As data becomes more accessible, retailers can better prepare for holiday returns. Whether updating their current policies, merchandising or staffing needs, they can change their current operational processes to increase efficiency and create a better experience for their customers.