Thursday, June 11, 2026
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Google to add AI performance report to Merchant Center


Google announced a new AI performance insights report in Merchant Center that will give ecommerce brands their first native look at how they appear across AI-powered shopping experiences — including AI Mode, AI Overviews, and the Gemini app.

Google Merchant Center AI performance insights dashboard with simulated data showing funnel breakdown and share of voice metrics

Image Source: Google Merchant Center Help

The report is rolling out in the U.S., Canada, Australia, India, and New Zealand over the coming months.

What’s inside the AI performance report

The new report includes four core data views:

  • Share of voice: Shows how often your brand surfaces in AI-driven experiences across Search and Gemini, benchmarking against brands similar to yours. This is a relative metric — not a traffic or ranking number — potentially marking a shift in how Google is asking ecommerce marketers to think about visibility.
  • Shopping funnel performance: Maps your AI visibility across the three stages buyers move through: discovery, evaluation, and purchase. Each stage surfaces different types of queries so you can see where your brand enters the conversation and where it drops out.
  • Product term insights: Identifies the popular product terms users are searching across Search conversations, along with your share of voice for each. Think of it as keyword data, filtered through what AI interfaces actually surface.
  • Product attributes insights: Surfaces the specifications buyers are searching for, giving Merchant Center feed optimization a more direct signal from AI-driven behavior.

What this means for marketers

This is the first time Google has offered native reporting on AI search visibility metrics for ecommerce. It’s a signal that AI performance is now its own measurement category.

The share of voice metric is particularly significant. Moving from position- or traffic-based reporting to a relative visibility metric puts AI search optimization on similar footing to paid media planning and non-AI search optimization.

For content and feed strategy, product term and attribute insights give ecommerce teams something they haven’t had before: a direct line from what AI systems retrieve to what product descriptions and category pages should actually say.

It’s also worth noting the timing. Bing rolled out its own AI performance report in Webmaster Tools earlier this year. Google is now building parallel infrastructure.

How to track AI visibility beyond Google’s ecosystem

Google’s new report only covers its own surfaces, and in a limited capacity. If you want a full picture of how your brand appears across ChatGPT, Perplexity, Google AI Mode, and Bing in one place, Semrush can give you the visibility you need. 

For smaller teams, Semrush’s AI Visibility Toolkit tracks citation frequency, cited URLs, and grounding queries across platforms.

AI visibility dashboard with highlighted AI Visibility score gauge and LLM mention analytics

And for enterprise teams that need competitive benchmarking and cross-platform tracking at scale, Semrush Enterprise AIO includes AI optimization tools for monitoring mentions, citations, and sentiment across LLMs.

AIO Overview dashboard showing share of voice, referral traffic, AI visibility, and ranking metrics
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