American tech company Google’s generative artificial intelligence (AI) aims to revolutionise online shopping, making complex purchase decisions faster and easier. The AI leverages Google’s Shopping Graph, a comprehensive dataset of constantly-changing products, sellers, brands, reviews, and inventory, housing over 35 billion product listings. The Graph is refreshed every hour with more than 1.8 billion listings.

The Shopping Graph, powered by machine learning, is a real-time dataset that stores specific information about products, including availability, reviews, pros and cons, materials, colours, and sizes. The graph is constantly updated through the Google Merchant Center or from what retailers and brands post across the web, Google said on its website.

One of the Graph’s key features is its ability to find products with specific criteria. For example, if one is searching for a women’s red puffer coat that’s cropped, shiny, has a fleece hood, is a size medium, is on sale, offers free shipping, is suitable for extreme weather and lightweight, the Shopping Graph scans billions of listings and relevant data from the web, such as images, descriptions, reviews, and YouTube videos. Then, it uses machine learning to understand relevant, nuanced characteristics of the desired product.

Moreover, the Shopping Graph powers shopping features such as ‘shop the look’, which shows popular ways to style an item, and similar products to consider. It also aids complex purchases with the buying guide feature. This feature, using natural language understanding, synthesises insights about a product from a wide range of trusted sources on the web, including articles and user reviews, allowing shoppers to see the most important information at a glance.

Fibre2Fashion News Desk (NB)

Disclaimer - All News/Articles items are subject to copyright and no article either in full or part may be reproduced in any form without permission from Fibre2Fashion Pvt. Ltd.