The lack of a universal sizing guide for footwear can yield frequent returns when a consumer doesn’t get the right fit. This has led to the emergence of new technologies that promise retailers more accurate recommendations. But new research from sizing data platform uSizy suggests that footwear is well positioned in the apparel market to reduce the return rate of ill-fitting product — as long as it focuses on measurements, not flash.
“The fit of a garment is different than a shoe,” said Susan Haigh, relationship manager at uSizy. “The fit is either right or wrong for shoes, and so consumers can quickly come to a clear conclusion. With clothing, there are many more variables.”
Data collected by uSizy from several sportswear brands, including Nike and Adidas, demonstrated that footwear segments consistently saw a lower return rate by 1-2% than apparel. Asics was the only outlier, with a return rate of 6.52% for footwear and 3.73% for apparel.
Footwear benefits from the brand loyalty of sneakerheads and the fact that it is easier to ensure consistency in shoe sizing within a brand. Technology has also played a part for uSizy customers. Brands and retailers have access to a database of information that tracks sizing and patterns across multiple companies. As shoe styles tend to vary less in design than apparel, fewer algorithms are needed to detect patterns and generate fit recommendations.
The research looked at 100,000 sales throughout 2019, therefore also taking into account the impact of new sizing tools like the app-based Nike Fit program. However, return rates were still 6–8% across all brands surveyed, and data from Nike showed a slightly higher return rate than Adidas, despite Adidas offering no consumer-facing fit solutions beyond a written sizing guide.
This suggests that the impact of these interactive technologies on return rates might be negligible when used in conjunction with a data-specific product. Many new tools focus on consumer engagement and ease — using a mobile app or mirror — rather than prioritizing the accuracy of a recommendation, through innovations like machine learning and big data. This creates a positive customer experience that may capture foot measurements, but might not result in a perfect fit recommendation, if there isn’t additional data to inform it.
“Without a doubt, these tools can help improve return rates, although it is insufficient,” said Haigh. “The more exact the process for obtaining user measurements, the more you can rely on information from user profiles. Companies are missing the next step, which is very complicated to develop internally since thousands of data points are required and their own e-commerce may be insufficient.”
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