Google Cloud is launching four new and improved AI tools to provide customers with a simpler online shopping experience and help retailers with in-store inventory management.
- A personalized search and browsing experience for ecommerce sites.
- An AI-powered solution for checking shelves in stores.
- An AI-driven product recommendation system.
- A tool that uses machine learning to develop products on websites.
Here’s more about each of the new devices.
Personalized search and browsing for ecommerce sites
Google Cloud has introduced an AI-based tool that personalizes what customers see when they search for an ecommerce website.
The technology leverages Google Cloud’s retail search solution, helping to create a more seamless and intuitive online shopping experience.
The AI system behind this new tool can identify customer preferences by analyzing their behavior such as what they look at, add to their cart, and buy.
It uses this information to tailor its search results and prioritize products for a more personalized experience. Personalization is specific to the retailer’s website and is not linked to customer activity on Google.
AI-based product sorting for ecommerce sites
Google Cloud is launching a new AI-powered tool for ecommerce websites to improve navigation and product discovery.
This feature uses machine learning to optimize the order of products on a retail website when shoppers select a category.
Ecommerce sites have traditionally sorted product results based on category sold lists or hand-crafted collections, choosing which clothing to choose based on the season.
The AI-driven system developed by Google uses a new strategy, using historical data to improve how products are sorted. This increases relevance, accuracy and sales opportunities.
This tool is now available as part of Google Cloud Discovery AI solutions for retailers.
AI-driven product recommendations
Improvements to Google Cloud Recommendations AI will make ecommerce sites more personalized, flexible and helpful for individual customers.
One new feature, page-level optimization, allows the site to dynamically determine product recommendations to display to the buyer.
This time-consuming user experience testing can reduce demand and result in higher user engagement and sales.
Additionally, a new feature for revenue optimization uses machine learning to provide more effective product recommendations, which can increase revenue per user session.
A machine learning model created in collaboration with DeepMind takes into account product categories, item prices and user behavior on an e-commerce site to determine the ideal balance between customer satisfaction and revenue growth.
Finally, a new “buy it again” model uses a customer’s past purchases to suggest future purchases.
These new tools are available to all retailers using Google Cloud.
AI-Powered Shelf Inspection of Retail Stores
Retailers have been using a variety of shelf-scanning technologies for some time, but their success has been limited by the resources needed to develop AI models to identify and categorize products.
Google Cloud has launched an AI solution for scanning shelves to help retailers identify all types of products based on visual and textual attributes.
The tool can improve product availability, increase visibility into existing inventory, and translate that into actionable insights to identify where restocking is required.
This technology is currently in preview but will soon be available to retailers worldwide. Google says the retailer’s data and images are their property, and AI can only be used to identify products and price tags.
Featured Image: Daniel Constante/Shutterstock
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