Google Merchant Center: New AI performance report

Google plans to expand Merchant Center with a new AI performance insights report. This will give e-commerce brands a structured view of how their products and stores are perceived and surfaced in AI-powered shopping experiences for the first time. The announcement marks another step in which classic product data feed management and modern AI visibility are moving closer together.

What the AI performance report promises

The new report is intended to show retailers and brands how they appear in environments where artificial intelligence controls product recommendations, answers, and shopping surfaces. Instead of relying solely on classic click and impression metrics from Performance Max or Shopping campaigns, Google is putting the spotlight on whether product data, feed quality, and store signals are sufficient for AI-powered experiences.

For online retailers, this means an additional measurement layer alongside organic listings, paid ads, and Merchant Center diagnostics. Those who previously knew mainly feed errors, price discrepancies, and policy notices will likely receive metrics and insights specifically tailored to AI-powered shopping experiences. Google itself describes the benefit succinctly: brands should be able to understand how they are presented in these new contexts.

Merchant Center as the central hub

Google Merchant Center remains the central data source for product data in Shopping, Performance Max, and increasingly in generative surfaces as well. The planned AI report fits this logic: visibility no longer arises only through classic SERP elements, but also through dialog-based and assistive shopping flows. Retailers who maintain clean feeds, provide structured attributes, and submit consistent price and availability information lay the foundation for being considered in AI-powered experiences at all.

In practice, the report is likely to connect to existing Merchant Center areas where performance, product status, and feed health are already visible. Whether Google will display pure presence metrics, quality scores, or specific product group placements remains open at the time of the announcement. For SEO and e-commerce teams, however, one thing is clear: data quality in the feed is becoming the decisive lever for AI visibility as well.

Relevance for SEO, GEO, and e-commerce marketing

From a search engine optimization perspective, the focus is shifting from pure ranking signals toward entity-based product representations. AI systems require clear titles, precise descriptions, clean categories, GTINs, brand information, and high-quality images. Missing or contradictory attributes can cause products not to appear in generative shopping answers at all. The new report could make such gaps visible and thus build a bridge between technical SEO in the feed and generative engine optimization.

For generative engine optimization, the development means that retailers will need to prepare their data so that AI models can interpret it reliably, not just optimize content for classic search results. This includes, among other things, unambiguous product names, user-oriented descriptions, structured specifications, and consistent brand information across all channels.

What retailers should prepare now

Even without a final detailed view of the report, sensible measures can be derived. First, teams should conduct a complete feed audit: Are all required attributes set? Do prices match between the store and the feed? Are variants mapped correctly? Are there rejected products or warnings that have gone unnoticed for weeks? These fundamentals still determine whether Google integrates product data in a trustworthy way.

• Formulate product titles precisely and with search intent in mind, without keyword stuffing.
• Provide high-quality product images with a consistent style and clear presentation.
• Align structured data in the store with Merchant Center feeds.
• Communicate reviews, return policies, and shipping information consistently.
• Ensure regular feed updates so availability and prices remain current.

In addition, coordination between paid, organic, and feed teams is worthwhile. Performance Max campaigns, organic product pages, and Merchant Center data should reflect the same factual truth. Contradictions between store content and feed attributes are a common reason for limited distribution—a risk that is likely to carry even more weight in AI-powered shopping experiences.

Measurability and strategic classification

The AI performance insights report addresses a gap in the current reporting landscape. Many retailers today know how ads perform, but far less about whether and how their products are visible in new AI surfaces. A dedicated report in Merchant Center would increase this transparency and make decisions easier to base on data. For agencies and in-house teams, this means new reporting obligations in monthly and quarterly reviews.

In the long term, Google could also indirectly set standards for which feed quality is considered sufficient for AI shopping. Brands that establish clean data processes early are better positioned as generative shopping experiences continue to grow. The report is therefore not just an analytics feature, but a signal: product data excellence is becoming a competitive factor beyond classic SERP rankings.

Technical requirements for product feeds

Beyond editorial feed maintenance, technical factors play a central role. XML or API-based feeds must be delivered reliably, without frequent timeouts or incomplete updates. Product IDs that remain unique across campaigns, analytics, and Merchant Center are especially critical. Correct mapping of currencies, taxes, and shipping zones also prevents misinterpretation in automated shopping systems. Those who ignore this technical foundation risk not only classic feed rejections, but also weak presence in AI-powered product answers.

In addition, supplementary attributes are gaining importance: material, target audience, energy efficiency classes, or size charts can be decisive depending on the industry. The more precisely retailers describe products, the easier it is for AI models to generate relevant recommendations. The planned report is likely to start here and show whether Google has enough context to meaningfully integrate products in AI shopping.

Outlook for online retailers

The announcement of an AI performance insights report in Google Merchant Center underscores that e-commerce visibility is increasingly measured at the intersection of feeds, AI models, and assistive shopping surfaces. Retailers should treat Merchant Center, store SEO, and feed maintenance as an integrated system. Those who professionalize data quality, attributes, and consistent product communication now create the foundation to not only read the new report later, but actively improve it.