Auburn University and the Auburn Center for Supply Chain Innovation (https://www.auburnscm.org/) had the pleasure of attending the RLA’s Annual conference in 2020 for a second time. We were particularly interested in how companies handle returns at the customer interface. Customer product returns are a recurring headache for retailers, distributors, and manufacturers. In 2018 alone, customers returned nearly $400 billion worth of purchases, close to 10% of total sales, according to the National Retail Federation. Companies seek strategies to reduce customers’ return rates and improve reverse logistics operations by balancing return options, especially in the omnichannel retail context. Much attention has focused on understanding how firms might reduce return rates. But returns are inevitable in retailing since it is impossible for consumers to fully resolve all uncertainty regarding the physical and psychological fit of the product prior to purchase. According to a report from the consulting firm Invesp, in 2018 approximately 30% of all items ordered online were returned, compared to only 9% of items purchased in physical stores. Specifically, returns for online purchase of apparel and footwear tend to be higher as customers struggle to discern differences in sizing and appearance. Below we discuss the current state of the returns industry and provide the initial findings from a recent study in the apparel industry.

Omnichannel retailing presents new challenges for product returns management as firms move towards integrating returns, information systems, and inventories that have been typically operated as separate entities. As denoted by Daugherty et al. (2019), omnichannel refers to the development of “a truly integrated approach across the whole retail operation that delivers a seamless response to the consumer experience through all available shopping channels” (p.5). Omnichannel unites all customer touchpoints to deliver a seamless customer experience. Consumers can browse, purchase, and return goods across a variety of channels. A seamless shopping experience requires retailers to embrace not only all channels of distribution but also all return channels in the omnichannel retail context. This returns channel includes many choices (i.e., return to the store, ship to the manufacturer’s/ retailer’s warehouse, ship to the manufacturer’s factory). Generally, the return to store option is considered most economical for retailers.

Stores with an omnichannel capability can minimize return costs across the network and get to an optimal final disposition fastest. According to an Alix Partners study (2017), the store returns process costs retailers an average of $3 per package and up to $6 per return when shipped to a distribution center. By contrast, it can cost up to $8 per return when processed through a third-party. Therefore, retailers are working to encourage store returns for online purchases to mitigate reverse logistics costs. Coresight research (2019) finds that buy-online-return-in-store (BO-RIS) has been growing across the globe with 38% of retailers reported an increase in BO-RIS in 2018. Furthermore, the adoption rate is particularly high for omnichannel vendors with 70.5 % U.S. omnichannel retailers offer BO-RIS. As the apparel industry transitions from multiple-channel retailing to omnichannel retailing, there is a unique chance to address issues at the customer interface.

It is critical to know a customer’s attitude towards making returns in store. Coresight research (2019) indicates that avoiding paying for shipping, receiving an immediate refund, and the convenience of in-store returns are the main reasons consumers use BO-RIS. The same report suggests that 34% of customers would use BO-RIS to make an exchange for another product. This finding presents a real opportunity for retailers to engage the consumer and potentially drive additional sales once the customer is in store. Existing research reveals that personal interactions between the buyer and seller are essential in creating customer lifetime value. However, little research has explored how to take advantage of this additional face-to-face interaction event as an opportunity to enhance customer relationships or drive sales.

Unlike sales events, return events are a high-risk/high-reward customer interaction point for retailers. High-risk means that a lack of trust and frustration can frequently arise, which may deteriorate customer relationships and damage customer lifetime value if not handled well. Unhappy customers may share their unresolved complaints with thousands of others through social media. A recent industry survey indicates that customers are more willing to share negative in-store return experiences with their family and friends, 86.9% of respondents. Only 83.3% would share a positive return experience (LoyaltyOne, 2015). Thus, the impact of a bad return experience is far more than losing one dissatisfied customer. Conversely, if handled well, retailers can use this additional customer interaction opportunity to mitigate customer dissatisfaction with the initial purchase and strengthen long-term customer relationships. Hence, it is important to examine the problems retailers have in handling customers’ returns at brick and mortar stores and then explore how the returns experience impacts customer relationships and customer shopping behavior.

To further explore the complexity of handling returns in omnichannel, our team analyzed customer data from the apparel industry about the returns experience. Our analysis reveals that one of the biggest challenges in the returns process is mismatched pricing in omnichannel retailing. The price mismatch between online and offline leads to more returns friction, less customer satisfaction, and perhaps opportunistic/unethical customer returns. Customers have come to expect greater transparency of event resolution than before. Retailers may need to invest in software that keeps the store informed of online price changes and tracks customer transactions. Seamless software makes it transparent to refund customers the amount they paid originally even with applied discounts.

The returns policy plays a role in the returns process, but more than only focusing on leniency dimensions. The customer cares about the execution of the returns policy during the returns process. Taking the policy concerns and operational activities together, retailers can enable visibility in the returns process by making information about various aspects of the returns process available to customers. As the omnichannel moves towards deeper returns integration, the ability to trace activities becomes a helpful tool for evaluating, monitoring and solving supply chain stakeholders’ concerns (Simatupang and Sridharan, 2002). Visibility of the policies and traceability of returns information may contribute to retailer transparency, given the type of information captured and the accuracy of that information (Sarac et al., 2010). Since many retailers now have massive amounts of data related to customer transactions and behaviors, it is within their reach to institute transparent return policies that can be adapted to individual customers. Thus, the transparent returns policy is conceptualized as having two dimensions. The strategic dimension incorporates visibility of the return policy emanating from external signaling to stakeholders, including frontline employees, retail managers, customers. The executive dimension provides traceability of refunds and returned products through retailer coordination across operations.

There is an opportunity to increase retail sales at the customer interface. If you are interested in exploring pathways to reach these goals, we would welcome your feedback.

References

Daugherty, P., Bolumole, Y. and Grawe, S. (2019), “The new age of customer impatience: An agenda for reawakening logistics customer service research”, International Journal of Physical Distribution & Logistics Management, Vol. 49 No. 1, pp. 4-32. 

Sarac, Aysegul & Absi, Nabil & Dauzère-Pérès, Stéphane, 2010. “A literature review on the impact of RFID technologies on supply chain management,” International Journal of Production Economics, Elsevier, vol. 128(1), pages 77-95, November.

Simatupang, T.M. and Sridharan, R. (2002), “The collaborative supply chain”, International Journal of Logistics Management, Vol. 13 No. 1, pp. 15-30.

Driansky A., Madden P. and Webb A. (2017), “Retail viewpoint: many happy returns for retailers.” Available at https://www.alixpartners.com/insights-impact/insights/retail-viewpoint-many-happy-returns-for-retailers/

Coresight Research (2019), “Innovator Intelligence: Solving Retail’s Most Expensive Problem With AI-Powered Returns Reduction.” Available at https://coresight.com/research/innovator-intelligence-solving-retails-most-expensive-problems-with-ai/

Loyaltyone (2015), “Scents of the season.” Available at https://www.spraytm.com/october-feature-scents-of-the-season.html

Saleh K. (2018), “E-commerce Product Return Rate – Statistics and Trends.” Available at https://www.invespcro.com/blog/ecommerce-product-return-rate-statistics/

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Jianliang Hao, M.S; Tyler R. Morgan, Ph.D.; and Glenn Richey, Ph.D.,
It is co-produced by Jianliang Hao (Ph.D. candidate, Auburn University), Tyler R. Morgan (Assistant Professor in Supply Chain Management, Auburn University), Glenn Richey (Harbert Eminent Scholar and Professor in Supply Chain Management, Auburn University)