As an e-commerce professional with over 25 years of experience, many of these in the rag trade, I understand the importance of providing accurate sizing information to customers. This is especially crucial when it comes to selling clothes internationally, where sizing can vary widely from one market to another.

One common mistake that many e-commerce professionals make is expecting customers to look at size charts and do the size translations themselves. This is a major problem, as customers are often unsure about what size to choose, resulting in lost sales, returns and associated costs for both the customer and the retailer.

To avoid this problem, it is important to display the local expected size at the point of adding to cart. This means that customers can quickly and easily choose the right size, without having to go through the hassle of looking up size charts. This can be achieved through a variety of methods, such as displaying size information in a pop-up window or through an easy-to-understand size conversion tool. Consider using personalisation tools to tailer the size display based on the visitor’s geographic location.

Another common issue is customers buying multiple sizes with the intention of returning some. This can be a huge problem for retailers, as it not only increases the costs associated with returns but also puts additional strain on the supply chain. To address this issue, retailers should consider implementing fit predictor tools that use returns data to predict the correct size for each visitor. By doing so, retailers can significantly reduce the number of returns due to sizing issues, resulting in a more efficient and cost-effective supply chain.

It’s important to note that while fit predictor tools can be incredibly useful, they may not be appropriate for all customers. Some customers may prefer to choose their own size based on their own preferences, rather than relying on a fit predictor tool. To address this issue, retailers should consider offering multiple options for sizing, such as allowing customers to choose between a loose or tight fit.

In addition to fit predictor tools, it’s also important to analyse returns data when conducting A/B tests. While A/B testing can be a valuable tool for improving conversion rates, it’s important to remember that visitors may not be buying multiple sizes, even if their average order value drops. By analysing returns data alongside A/B test results, retailers can gain a more accurate understanding of how changes to their site are impacting customer behavior and adjust accordingly.

Finally, it’s important to remember that there is a difference between size and fit. Size is an absolute measurement, while fit is subjective and depends on personal preference. As such, it’s important to offer multiple options for sizing and to provide detailed product descriptions that take into account factors such as fabric stretch, cut, and style. By doing so, retailers can provide customers with the information they need to make an informed decision about what size to choose, while also ensuring that customers are satisfied with the fit of the clothes they receive.

In conclusion, selling clothes internationally can be a challenging task, but by providing accurate sizing information and utilising fit predictor tools, retailers can significantly reduce the number of returns due to sizing issues. By analysing returns data and offering multiple options for sizing, retailers can provide customers with a better shopping experience, while also ensuring that their supply chain remains efficient and cost-effective. So, take the time to get your sizing right, and your customers will thank you for it!

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