It is well-understood in retail that some products are more amenable to online sales channels than others. On one hand, consumers are comfortable with digitally assessing products whose attributes are well-known or can be fully understood without any physically interaction (e.g. batteries). On the other hand, for many products a digital assessment does not remove all uncertainty. Apparel is a classic example of such a product, since consumers might be hesitant to buy a clothing item without first physically trying it on.
In their recently published paper, Professors Santiago Gallino and Antonio Moreno (of Dartmouth College and Harvard University, respectively) investigate an emerging technology that is intended to address this consumer uncertainty: virtual fitting rooms. With this technology, a consumer can digitally replicate the in-store try-on experience by creating a virtual model of themselves, including key body measurements as well as skin tone and hairstyle. The idea behind such technology is to provide better information to consumers, which could lead to a number of better outcomes for the retailer. Of particular interest to the reverse logistics community, the authors test whether virtual fitting rooms reduce the probability of returns, as well as the probability of consumers ordering multiple sizes of the same product (a “home try-on” approach that is likely to include an unequivocal intention to return some items). They investigate their research questions using a series of carefully designed, randomized A/B tests, implemented by a large online apparel retailer in Latin America. Their findings have real implications for online retailers struggling with the problem of returns. Specifically, in one of the studies described in their paper, the authors show that, all else equal, the online fitting room technology reduces the probability of an item being returned by about 5%. In a subsequent study, they find no less than a 25% reduction in “home try-on” behavior when the virtual fitting room is utilized. The magnitude of these reductions is remarkably high, translating into substantial potential savings in returns processing costs for online retailers.
The above is a summary and commentary based on: Gallino, S., and A. Moreno (2018) “The Value of Fit Information in Online Retail: Evidence from a Randomized Field Experiment” Manufacturing & Service Operations Management, 20(4), 767-787.
This recurring series provides plain-English summaries of leading academic research in the area of consumer returns. It is co-produced by Mark Ferguson (Univ. of South Carolina), Michael Galbreth (Univ. of Tennessee), and Guangzhi Shang (Florida State Univ.).