In advance of the National Retail Federation 2023 show in New York City, Google Cloud is launching a variety of new AI tools for retailers. These include a shelf-checking tool to help retailers more effectively keep their inventory stocked, an updated ecommerce technology for better product discovery, and a new personalization capability to provide more personalized search and recommendations.
One of the new tools is a shelf-checking solution that uses AI to recognize products at scale from video and photos taken by ceiling-mounted cameras, store robots or other devices. Those images are then fed into Google Cloud for Retailers, which uses a machine learning engine to recognize and analyze the items on the shelves.
Another new AI-powered tool is a product recommendation system that provides shoppers with recommendations based on their past purchases and shopping habits. This is particularly useful for recommending repeat purchases, which can boost “revenue per user session” and increase customer satisfaction.
A third tool is an enhanced version of Google’s existing in-store product recognition feature. It will help retailers more effectively manage inventory, improve e-commerce experiences and eliminate the need for manual labor by using an AI engine to recognize and analyze products from store-supplied videos or pictures.
The in-store shelf checking technology can recognize billions of items based on their visual and text features, and translate the data into actionable insights to help retailers improve their product availability, enhance visibility into inventory, and identify where restocks are needed, according to Google.
In addition to the shelf-checking technology, Google Cloud also launched a new personalization capability for websites that personalizes results for customers based on their interests and previous buying patterns. This can help customers find the right products and save time on searches.
This can be helpful to a wide range of shoppers, from fashion-forward women’s apparel shoppers to moms searching for the latest must-have kitchenware. The AI-powered system learns over time from the historical product ordering and popularity of products, so it can optimize the order of product listings on websites.
As a result, this can help retailers save money on labor costs and improve e-commerce experiences by more quickly providing the latest product selections to shoppers. The system also helps retailers improve their website’s ranking in search results and drive more traffic to their online stores.
Lastly, Google Cloud introduced a new browse feature that helps retailers improve their digital storefronts by enhancing the browsing experience of customers. The AI-powered system can automatically curate a product list for a retailer’s site, brand or landing page.
The personalization capability is a step up from Google’s Retail Search tool, which allows a retailer to provide shoppers with personalized results for their search queries. The new browse feature is part of the company’s Discovery AI solutions for retailers, and can be used to turbo-charge a retailer’s website with more dynamic and intuitive shopping experiences. Finally, the company is introducing updated machine learning models to its Recommendations AI service that are able to provide double-digit uplifts in conversion and clickthrough rates, as well as new revenue optimization and buy-it-again model capabilities. The Recommendations AI solution also enables retailers to dynamically improve product ordering and recommendations panels on e-commerce sites and deliver personalized suggestions for repeat purchases.