Reversing the 'sizeable' problem of fashion returns

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Reviews and social proof could prove key in reversing the issue of fashion returns the latest research from Yotpo, the eCommerce marketing platform, reveals.

With online returns predicted to balloon into a £5.6billion problem for retailers by 2023*, original research of over 2,000 UK fashion shoppers in the 'Fashion eCommerce Report: Consumer Trends and Strategies for Brands' from Yotpo revealed 78% of UK fashion shoppers had returned up to £500 in the last year alone, rising to 81% among 14 – 21 year olds. 

Fit and quality issues proved the top reasons prompting fashion returns for 83% of UK shoppers, followed by items appearing different in the flesh compared to what they looked like online for a further 47%. 

When it comes to sizing reassurance when shopping online, 63% of shoppers turn to user-generated content, such as reviews, to get further clarity on fit information, while 86% said that real-life photos of other customers wearing items of clothing were important when validating how a product would look like or fit them. 

This, the report suggests, shows the critical roles of reviews and social proof, not only in assisting with online conversions but also, ultimately, reducing returns, as Talia Shani, Director at Yotpo, explained:

"We know that confidence around sizing is a significant contributor to both conversions and returns, so it's imperative that online fashion retailers support the buying journey at each stage by instilling confidence in the size, style and fit of a product.  Luckily, simple changes to the online UX can support this."  

"By having reviews from other customers displayed alongside product imagery, or showing user generated content, such as photos and videos from other shoppers, can help customers validate their buying decision, making them more likely to convert and less likely to make a return – a win-win for the retailer," she concluded.

Research conducted by Pollfish on behalf of Yotpo on July 1st. Sample size: 2,000 UK adults

* GlobalData, 2019