Amazon’s AI fit recommendation

Amazon uses AI and machine learning models to recommend which size of a clothing item is most likely to fit a consumer. The recommendation is based on other data consumers have shared in the past.

The ecommerce retailer’s algorithm groups together consumers who purchase similar sizes of clothing and demonstrate similar preferences for how they want their clothes to fit. Apparel items with similar fits — for example, oversized or slim fits — are also grouped together. The algorithm accounts for a particular item’s details, size chart, customer reviews return rate and data about consumers who purchased the item.

Amazon uses that information to make an intelligent recommendation on size. That’s based on what consumers who typically buy the same size have bought and kept. The algorithm also adapts to changing sizes, Amazon says. For example, it will recommend a larger children’s size than the one purchased in previous months.

The fit recommendation tool analyzes millions of data points each day to generate billions of size recommendations per month, according to Amazon. And that leads to better conversion results. Customers — the company claims — are more likely to purchase, and less likely to return a clothing item when a size is recommended to them.

Source: Amazon explains how it uses AI to improve apparel conversion