Google expands AI commerce tools ahead of the holiday shopping season

Google is expanding its suite of agentic commerce tools to help retailers reach shoppers who are increasingly using artificial intelligence to search for, compare, and purchase products. Ahead of the holiday shopping season, the company introduced new capabilities for advertisers and online retailers. They include tools for measuring brand visibility in AI-powered search, integrating Business Agent with YouTube advertising, and expanding Universal Commerce Protocol capabilities in Merchant Center. Google expands AI Search visibility measurement Google has made AI Performance Insights in Merchant Center available to businesses in Australia, Canada, India, New Zealand, and the United States. The tools allow retailers to evaluate how often their products and brands appear across different Google services powered by artificial intelligence. In particular, companies can see their share of visibility compared with other brands across formats such as AI Mode and AI Overviews. This is an important addition to traditional search advertising and organic search analytics. As users increasingly receive product information directly through AI-generated answers, businesses need to understand not only how they rank in search results but also how their products are represented in AI responses. Business agent comes to YouTube Ads Google is also testing a new way for shoppers to interact with brands on YouTube. The company is inviting eligible U.S. retailers to participate in the beta test of Business Agent integrated directly into YouTube ads. This format allows users to ask detailed questions about a product and receive personalized answers without leaving YouTube. For example, a user may see a product in a video ad and immediately get additional information about its features, sizing, fit, or other characteristics. As a result, the journey from the initial product discovery to further research can take place within the same environment. Google previously introduced Business Agent in Search as a tool that allows brands to provide shoppers with conversational assistance. Now, a similar approach is being extended to YouTube advertising. Universal commerce protocol expands checkout capabilities Another area of the updates involves Universal Commerce Protocol, or UCP. Google is expanding the UCP integration hub in Merchant Center. The protocol is designed to standardize interactions between AI agents and commerce platforms during shopping-related transactions. One of the key updates is the ability to use UCP for checkout. Merchants using UCP-powered checkout can now enable additional features, including: transferring the shopping cart to their own website; expanded testing of the checkout process; other capabilities that Google plans to add in the future. Analytics features are also expected to become available in future updates. The new UCP capabilities are gradually rolling out in the United States. They are expected to become available in Australia and Canada early next year as well. Tapestry is already using UCP to sell products One example of UCP in action is Tapestry, the company behind brands such as Coach and Kate Spade. Ahead of the holiday shopping season, the company used UCP-powered checkout to make products available for purchase directly through Google Search, including AI Mode, as well as the Gemini app. This demonstrates how the traditional online shopping model is gradually changing. Previously, users would typically move from a search engine to a retailer's website, find the product they wanted, add it to their cart, and complete the purchase. AI commerce can reduce the number of these steps by allowing users to research products, get answers to their questions, and move toward a purchase directly within an AI-powered environment. Product feed quality remains important Despite the focus on AI agents and new technologies, Google continues to emphasize the importance of a fundamental part of e-commerce: high-quality product data. Accurate and detailed information in Merchant Center remains critical for ensuring that products can be properly displayed and recommended across AI-powered environments. Google reports that merchants following the basic recommendations for setting up their Merchant Center feed see, on average, 5% more conversions in the following month. During testing with Lululemon, Google also found that additional conversational attributes provided by the retailer were used in 50% of relevant product recommendations in AI Mode. This shows that AI systems need more than just the presence of a product in a catalog. They also need comprehensive information that helps them understand the product's characteristics and how well it matches a user's query. Therefore, e-commerce companies should pay attention not only to advertising campaigns but also to the structure, accuracy, and freshness of their product feed data. Google adds loyalty program data Another new Merchant Center capability is related to loyalty programs. Retailers can connect data about their loyalty program members to Merchant Center. This allows Google to show users personalized prices and benefits available to loyalty members. For example, members of Minted's Minted More program can see a special price for holiday cards when searching for products. As a result, AI commerce is gradually moving beyond general product recommendations and taking additional context into account, including information about individual shoppers and their loyalty program status. What this means for advertisers and retailers Google's new tools are changing how brands approach visibility in search and e-commerce. For businesses, it is becoming important not only to ensure that products are indexed or to launch advertising campaigns. Companies also need to make their product information easy for AI systems to understand so that it can be accurately used in responses to user queries and product recommendations. In the new ecosystem, a shopper may: See a product in a video ad. Ask an AI agent about its features. Receive personalized information. Compare the product with other options. Add the product to their cart. Proceed to checkout. Part of this journey can take place without the traditional need to move between multiple pages and services. That is why product data quality, integration with AI tools, and the ability to provide a seamless purchasing journey are becoming increasingly important for e-commerce businesses. What businesses should consider The development of AI commerce means that companies need to reconsider how they manage product information. First and foremost, businesses should make sure that their Merchant Center data is accurate, up to date, and sufficiently detailed. Product names, descriptions, specifications, prices, availability, and other attributes should match the actual information on the website. Businesses should also pay attention to additional attributes that can help AI systems better understand the context of a product. Integrating loyalty programs can be another area to consider, particularly for businesses that offer personalized pricing or other benefits to returning customers. For large e-commerce projects, technical readiness for new checkout methods and integrations with AI agents is also becoming increasingly relevant. Conclusion Google is gradually expanding its e-commerce ecosystem beyond traditional product search and advertising toward AI-agent interactions across the entire customer journey. New Merchant Center capabilities allow businesses to measure their visibility in AI-powered results, Business Agent brings product consultations into YouTube advertising, and Universal Commerce Protocol is developing standardized mechanisms for interaction between AI agents and commerce platforms. At the same time, the foundation of e-commerce remains unchanged: businesses need to provide accurate, complete, and up-to-date product information. The holiday shopping season will be an important practical test for these new AI commerce formats. It will show how effectively conversational tools can help move users from product discovery to purchase and what additional results retailers can achieve by investing in high-quality product data and AI integrations. Read this article in Ukrainian.