Fits like a glove? Knowledge and use of size finders and high-end fashion retail returns

Abstract

With returns imposing a growing burden on retail supply chains, major e-commerce platforms are increasingly implementing size recommendations to curb returns. Based on a fit valence and fit reference framework, we test whether customers using the size finder are more likely or less likely to return products. We use confidential data from a major fashion e-commerce platform in Sweden that introduced a size finder based on customer-supplied information on weight, build, hips, waist, shoulders, leg-to-torso length, and body shape. In a sample of 496,365 items ordered by 75,707 customers from 113 countries between July 2015 to April 2022, those using the size finder are 0.65% more likely to return an item. The findings are robust to a variety of econometrics tests. Furthermore, machine learning analysis based on gradient boosted trees shows that size finder is among the least important features in predicting returns. However, for each unit quarterly increase in the use of the size finder with purchased items, the customer lifetime value (CLV) increases by 7.51% in the next quarter and 5.53% in the subsequent quarter. Post-hoc interviews with executives in the e-commerce sector demonstrated that, when implementing size recommendation tools, managers in fashion retailers must weigh a small increase in returns against higher CLV from repeat customers.