Fit Review Highlights offer relevant customer feedback
Another feature that helps Amazon customers find the right fit is AI-generated Fit Review Highlights. Amazon creates a review highlight for each customer based on their recommended size using common themes across reviews, with the goal to make it easier for customers to get personalized size guidance.
The feature tells a customer whether to size up or down in a particular style based on reviews from customers who have purchased the item in the same size.
“We use the latest and most advanced forms of AI, like large language models (LLMs), to extract details from customer reviews, such as size accuracy, garment fit on specific body areas, and fabric stretch,” explains Chaudhri. “We then use AI to summarise these details in an easy-to-read review highlight. The highlight guides each customer to the most relevant information, so they don’t have to manually parse through hundreds of reviews for each item.”
Reimagining clothing size charts with trusted AI-powered data
Amazon is also using AI to make size charts more accurate and useful for customers, while showing customers relevant information in a more visually engaging way.
By leveraging LLMs, Amazon automatically extracts and cleans product size chart data from multiple sources. This data is then transformed into standardized sizes, with duplicate information being removed and missing or incorrect measurements being auto-filled, resulting in a more accurate and consistent size chart.
AI Fit Insights Tool enables brands to improve their product offerings
As Chaudhri describes, brands and selling partners can benefit from all of this innovation, too. “Understanding why customers returned an item can be a mystery, but with our new Fit Insights Tool, Amazon can do the heavy lifting for brands and offer insights into the fit of various products,” he adds.
Amazon’s Fit Insights Tool uses an large language model to extract and aggregate customer feedback on fit, style and fabric. It contextualizes returns and size chart analyses with customer reviews, using machine learning to identify defects in size charts. By leveraging this data, brands can better understand customer fit issues, improve how they communicate sizing to customers, and even incorporate the feedback into future designs and manufacturing. This helps brands reduce fit-related returns and more accurately list their items for customers.
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