To minimise apparel returns when shopping online, the company developed four features that use large language models, generative AI, and machine learning to help customers find their accurate sizes for clothing. Through this, Amazon intends to reduce the time spent finding the correct size by enabling AI and machine learning models to recommend a size based on each product’s detail page. Amazon Fashion’s commitment is to enhance the shopping experience and meet the needs of customers while bringing an improved selection to its stores.
Amazon’s AI-based features and their capabilities
Furthermore, Amazon introduced an AI-generated Fit Review Highlights feature that develops a review highlight for each customer considering their suggested size using mutual themes across evaluations. The newly added feature informs the customer whether to size up or down in a style based on reviews from other users who bought the item in the same size. Amazon leverages large language models to extract data from customer reviews, such as size accuracy, fit on specific body areas, and fabric stretch. Details are then summarised using AI in a user-friendly review highlight that guides customers to the relevant information. Size charts were also improved by using large language models that automatically extract product sizes, remove duplicate information, and auto-correct missing or incorrect measurements, making them more accurate and consistent. The company is currently experimenting with additional methods of providing the most relevant size and measurements for each user, including grouping measurements for their respective size.
In addition to providing customers with enhanced services, Amazon supports brands and selling partners with the new features. Leveraging a large language model to extract and aggregate customer feedback on fit, style, and fabric, the company’s Fit Insights Tool allows sellers to receive contextualised information on why a product was returned. The feature uses machine learning to identify defects in size charts. Brands can use this data to understand customer fit issues, enhance their size communication, and incorporate feedback into future designs and manufacturing.