Amazon Fashion has revealed its intention to use artificial intelligence ( AI ) to assist online clothing shoppers in selecting the right size.
The company created four features to assist customers in finding their precise clothing sizes using big language models, conceptual AI, and machine learning in order to reduce apparel returns when shopping online. By allowing AI and machine learning models to suggest a size based on each company’s information page, Amazon hopes to shorten the time it takes to find the right size. The goal of Amazon Fashion is to improve customer satisfaction and the buying experience while bringing better products to its shops.
Amazon’s AI-based features and their functions
Additionally, Amazon introduced an AI-generated Fit Review Highlights element that creates a review highlight for each customer based on their suggested size using themes that are shared across evaluations. Based on testimonials from other people who purchased the same size object, the recently added feature tells the customer whether to size up or down. Amazon uses huge language models to extract information from customer reviews, including fabric stretch, fit on particular body areas, and size accuracy. Next, using AI, details are summarized in a user-friendly review emphasize that directs customers to the pertinent data. By using large vocabulary models that quickly remove product sizes, eliminate duplicate info, and auto-correct missing or incorrect measurements, making them more accurate and consistent, size charts were also improved. The business is currently experimenting with new ways to give each customer the most appropriate size and measurements, including grouping measurements according to their respective sizes.
Amazon supports businesses and selling lovers with the new features in addition to offering customers better services. The bank’s Fit Insights Tool enables sellers to receive contextualized details on why a product was returned by utilizing an extensive vocabulary design to remove and index client feedback on fit, style, and fabric. The element uses machine learning to spot sizing chart flaws. This information can be used by brands to better understand consumer meet issues, improve size conversation, and incorporate suggestions into upcoming designs and manufacturing.