Google Cloud is launching four new and updated AI tools to provide customers with a smoother online shopping experience and help retailers manage in-store inventory.
- A personalized search and browsing experience for e-commerce websites.
- An AI-powered solution for checking store shelves.
- AI-driven product recommendation system.
- A tool that uses machine learning to rank products on websites.
Here’s more about each of the new tools.
Custom search and browsing for e-commerce websites
Google Cloud has introduced an AI-based tool that personalizes what customers see when they search and browse an e-commerce site.
This technology enhances the capabilities of the existing Retail Search solution in Google Cloud, helping to create a smoother and easier online shopping experience.
The AI system behind this new tool can identify customers’ preferences by analyzing their behavior, such as the items they view, add to their cart, and purchase.
It uses this information to fine-tune search results and prioritize products for a more personalized experience. The personalization is specific to the retailer’s site and is not related to the customer’s activity on Google.
AI based product sorting for ecommerce websites
Google Cloud launches a new AI-powered tool for e-commerce sites to improve browsing experience and product discovery.
This feature uses machine learning to improve the ranking of products on a retailer’s website when shoppers select a category.
E-commerce sites traditionally sort product results based on bestseller lists or hand-created collections, such as choosing which garments to highlight based on the season.
The AI-driven system developed by Google adopts a new strategy, using historical data to improve how products are sorted. This can increase relevancy, accuracy, and chances of a sale.
This tool is now available as part of Google Cloud’s Discovery AI solutions for retailers.
AI-powered product recommendations
Upgrades to Google Cloud Recommendations Artificial intelligence can make e-commerce sites more personalized, dynamic, and helpful to individual customers.
One new feature, page-level optimization, allows the site to dynamically select product recommendations to show to the shopper.
This can reduce the need for time-consuming user experience testing and can lead to higher user engagement and sales.
Additionally, a new revenue optimization feature uses machine learning to provide more effective product recommendations, which can lead to more revenue per user session.
Created in collaboration with DeepMind, a machine learning model considers product categories, item prices, and user behavior on an e-commerce site to determine the ideal balance between customer satisfaction and revenue growth.
Finally, the new Buy Again model uses a customer’s past purchases to suggest future follow-up purchases.
These new tools are now available to all retailers that use Google Cloud.
AI-powered shelf scanning for retail stores
Retailers have been using various shelf-scanning technologies for some time, but their success has been hampered by the resources needed to develop AI models for product differentiation and classification.
Google Cloud has launched an AI shelf-scanning solution to help retailers identify products of all kinds at scale based solely on visual and textual features.
The tool translates data into actionable insights that can improve product availability, increase visibility into existing inventory, and identify where restocking is required.
This technology is currently in preview but will soon be available to retailers around the world. Google notes that the retailer’s data and images remain their property, and AI can only be used to recognize products and price tags.
Featured image: DANIEL CONSTANTE / Shutterstock
