The holiday season is always an exciting time for retailers as they experience a boom in new customers and revenue. However, with the large spike in sales also comes the potential for a large amount of returns.
So, what can retailers do to combat an increase in returns? As business problems vary and become more complex, advanced analytics offer a set of tools for not only predicting the rate of returns, but also preparing retailers to take actions to correct some of the reasons or behaviors for returns.
As retailers prepare for next holiday season, there are two specific issues that need to be resolved: how to reduce the cost of returns, and how to design return channels that are more customer friendly.
Reducing the Cost of Returns
Returns are not only time consuming for retailers, they're also expensive. To extract maximum sales out of their returns, retailers can classify returning items into one of five categories: return to manufacturer; return to store back room; refurbish; reuse, recycle or donate; or dispose of the item returned. Using this kind of classification system can help reduce expenses as it avoids sending each individual item through the entire supply chain path before reaching its appropriate destination.
Retailers can also leverage big data systems to track orders at the customer level, which will help reduce overlaps in the forward and reverse logistic processes, and eventually reduce costs. Advanced analytics can also be leveraged to identify returnable items and target the relevant customer base for easy returns.
Omnichannel retailers should also encourage their customers to make purchases online and then open the channel for returns in a physical store, as this cuts down expenses in reverse logistics operations. The high costs of returns can also be mitigated by using sophisticated network optimization algorithms to ensure more collaboration between third-party logistics providers and retailers — and to determine optimized hand-off locations.
Designing Customer-Friendly Return Channels
When designing lower-cost return channels, retailers must remember to always think of the customer first. Customer contact centers can use real-time capabilities like mapping and recognizing customers, which will allow them to roll out customized offers based on the customer’s lifetime value. Return policies can also be customized for products based on the product's shelf life, customer segmentation of purchase, and the logistics of shipping the product back for resale.
Another option is product feature extraction. This technique can help retailers make decisions about product returns that require robust packaging. One option would be to place return labels in packaging to provide a seamless experience for the customer, as opposed to the customer having to print out the return label. Finally, other customer-centric strategies can be deployed, such as granting store credits to omnichannel users, and offering automatic refunds or free shipping on returns to all customers. All of these options are likely to generate return customers.
While retailers saw a wealth of purchases this past holiday season, the costs of returns are just beginning to be felt. By using the above tips, retailers can reduce the burden of returns to both themselves and to customers. This will create a more positive shopping experience and turn what was once viewed as a negative action into a positive outcome.
Sandeep Uniyal is the engagement manager at Mu Sigma and Krishna Rupanagunta is the geography head at Mu Sigma, a big data analytics company.
Sandeep Uniyal is the engagement manager at Mu Sigma.Â
Krishna Rupanagunta is the geography head at Mu Sigma.Â