--- title: "Merchant Center AI Performance Insights Guide | Webtures" description: "How does Merchant Center’s AI performance insights report measure your brand share in AI Mode and AI Overviews, and which actions does it reveal? A" source_url: "https://www.webtures.com/insights/merchant-center-ai-performance-insights-guide/" lang: "en" updated: "2026-10-06T00:00:00.000Z" --- # Reading your brand share in Merchant Center AI performance insights Short Answer How does Merchant Center’s AI performance insights report measure your brand share in AI Mode and AI Overviews, and which actions does it reveal? A guide. Selen Çetin 8 min read Summarize with SI ![Reading your brand share in Merchant Center AI performance insights](https://www.webtures.com/images/insights/merchant-center-ai-performance-insights-guide/cover.svg?v=si1) ![Reading your brand share in Merchant Center AI performance insights](https://www.webtures.com/images/insights/merchant-center-ai-performance-insights-guide/cover-light.svg?v=si1) [Selen Çetin](https://www.webtures.com/authors/selen-cetin/) Visibility Intelligence Specialist Published: 06 Oct 2026 Updated: 06 Oct 2026 AI performance insights is a report in Google Merchant Center that shows how visible a brand and its products are compared with competitors in conversational queries with shopping intent on AI Mode and AI Overviews. On 16 September 2026, Google made the report generally available to businesses in Australia, Canada, India, New Zealand and the US. The report aims to surface the part of long, complex conversational queries that gets lost in classic keyword reports. It splits the brand’s share of voice into discovery, evaluation and ready-to-buy stages, and lists the terms users prioritise and the attributes missing from product data. This makes the report not just a measurement screen, but a direct to-do list for improving the product feed. However, reading the numbers without understanding how the report calculates them and where its limits lie can lead to the wrong priorities. In this guide, we cover what the report measures, how to interpret share of voice and how brands selling from Türkiye into these markets can use the report today. ## Which question does the report answer? The AI performance insights report answers the question: “How much does my brand appear in conversational shopping queries compared with my competitors?” Users ask multi-condition questions in AI Mode, such as “a breathable shoe that stays comfortable on long runs for someone with flat feet”. Because these queries cannot be reduced to a single keyword, they do not form a meaningful row in classic performance reports. Google’s new report groups these queries by intent and shopping stage and shows the brand’s share of these conversations. The report is found in Merchant Center under the Analytics tab, in the Products section, via the “AI performance” tab at the top of the page. Data can be narrowed with product category, time period and country filters. The report has no view that combines all categories on one screen; each category needs to be reviewed separately. This may look inconvenient at first, but it enforces the right approach: a cosmetics brand’s visibility in skincare and make-up can follow very different dynamics, and that difference should not get lost in averages. ## How is share of voice calculated, and why can it mislead? Share of voice is calculated as the brand’s SI impressions for related queries divided by the total impressions of the brand and its competitors defined in Merchant Center. The critical detail in this definition is “defined competitors”. The competitor set comes from Merchant Center’s own competitor definition and cannot be changed by the user. The percentage you see therefore reflects your share within the competitor group Google has defined for you, not your share among all brands in the market. This calculation logic can create several misleading situations, and Google’s help documentation states them clearly: - **100 percent share of voice:** If the account has no defined competitors, the share shows as 100 percent. This is not a success; it means no comparison is possible. - **Zero value:** When impressions are insufficient, share of voice shows as zero. - **Dash:** When there is no impression data at all, a dash appears instead of a value. - **Rising together:** When the competitor set changes, both your share and your competitors’ average share can rise in the same period. - **A few days’ delay:** Data updates daily but arrives with a lag of a few days. Before interpreting a change in share of voice, it is therefore worth checking whether the competitor set has changed and whether impression volume is meaningful. In small categories especially, a few days of fluctuation may reflect data scarcity rather than a structural shift. ## How should the discovery, evaluation and ready-to-buy stages be read separately? [GEO](https://www.webtures.com/generative-engine-optimization-geo/) · SI VisibilityIs your brand visible in generative search?Let's build a strategy to surface your brand in ChatGPT, Gemini and Perplexity answers.[Get in touch →](https://www.webtures.com/contact/) Free AssessmentMeet a digital strategy team operating since 2011Share your goals and we'll map a visibility roadmap tailored to your brand.[Get in touch →](https://www.webtures.com/contact/) Measurable GrowthUnite GEO and performance marketing in one modelLet's generate sustainable digital demand with a data-driven approach.[Get in touch →](https://www.webtures.com/contact/) The report splits conversational queries into three stages, discovery, evaluation and ready to buy, and share of voice needs to be read separately for each. Discovery covers early-stage intents where users explore general product options, evaluation covers mid-stage intents where users compare options or ask about specifications, and ready to buy covers late-stage intents close to a transaction. Within each stage, the report also shows search types such as searching by category, researching product specs or looking for reviews. The table below summarises what low share of voice can indicate at each stage and which action can be prioritised. | Stage | Typical User Behaviour | What Can Low Share of Voice Indicate? | Priority Action | | --- | --- | --- | --- | | Discovery | Explores general options and tries to understand the category. | Product titles and category mapping do not match the user’s language. | Clarify the category terms users use in titles and descriptions. | | Evaluation | Compares options and looks for specifications and reviews. | Attributes used in comparisons are missing from the feed or review data is weak. | Fill in popular attributes and strengthen product review and rating data. | | Ready to buy | Confirms price, stock, delivery and return terms. | Price, stock or shipping information is outdated or less clear than competitors’. | Review price and stock synchronisation and the shipping and return fields. | The difference between stages also shows where the problem lies. A brand that is strong in discovery but weak in evaluation is getting onto users’ radar but may be eliminated in comparison. Conversely, a brand that is weak in discovery but strong at the ready-to-buy stage may be standing out mainly in queries from users who already know it. ## How do you turn the top terms and popular attributes cards into feed actions? The top terms and popular attributes cards are two to-do lists that directly show which words and fields are missing from product data. The top terms card lists the terms users prioritise in conversational queries within a category, such as “maximum cushioning” or “arch support” for running shoes. The popular attributes card shows which structured technical specifications users look for, such as size, colour or material, are missing from product data. The third card, top search intents, explains the intent behind queries beyond the keyword. Google recommends starting improvements with the most popular terms and missing attributes. When applying this, the following order offers a practical path: - **Fill in missing attributes first:** Structured fields are less open to interpretation than copy changes and create direct matches. - **Then focus on high-frequency, low-share search types:** Areas with high demand where the brand lags offer the fastest gains. - **Use terms only if they genuinely describe the product:** If your product has no arch support, adding the term may bring impressions in the short term but will create returns and lost trust. - **Date your changes:** Recording what changed in which product group and when makes it possible to interpret changes in share of voice correctly. ### Where should adding terms to titles stop? Adding terms to titles should stop at the point where it starts to hurt the readability of the product name. Trying to fit every term from the report into the product title weakens both the listing users see and how SI understands the product. The title should carry what the product is and its one or two most distinctive features; the remaining terms should be distributed across the description, product highlights and relevant attribute fields. ## What can the report not see? The AI performance insights report measures only organic visibility on Google’s AI Mode and AI Overviews surfaces; it does not cover paid ad traffic or SI platforms outside Google. The traffic filter in the report is currently limited to organic SI traffic such as free listings. The report is also available only for English-language queries in Merchant Center accounts in the five countries listed. You cannot see your brand’s position in AI Mode for Turkish queries with this report. These limits show that using the report alone as an SI visibility indicator would be incomplete. The same user may research a product in AI Mode, compare it in ChatGPT and read reviews in Perplexity. In Webtures’ [GEO consulting](https://www.webtures.com/generative-engine-optimization-geo/) approach, this Google data from Merchant Center is combined in the same view with the brand’s representation in other SI answers, making it possible to separate product groups that are strong in Google but weak in ChatGPT within a category. For Turkish queries and platforms outside Google, the gap the report cannot see is filled by tracking target prompt sets regularly with a [GEO tool](https://brantial.ai/) such as Brantial. ## How can brands selling from Türkiye use the report today? [GEO](https://www.webtures.com/generative-engine-optimization-geo/) · SI VisibilityIs your brand visible in generative search?Let's build a strategy to surface your brand in ChatGPT, Gemini and Perplexity answers.[Get in touch →](https://www.webtures.com/contact/) Free AssessmentMeet a digital strategy team operating since 2011Share your goals and we'll map a visibility roadmap tailored to your brand.[Get in touch →](https://www.webtures.com/contact/) Measurable GrowthUnite GEO and performance marketing in one modelLet's generate sustainable digital demand with a data-driven approach.[Get in touch →](https://www.webtures.com/contact/) Brands selling from Türkiye to the US, Canada, Australia, New Zealand or India can use the report today in the Merchant Center accounts they have set up for these markets. For e-export brands in textiles, home decor, cosmetics and food, this means seeing the language of conversational queries in the target market first-hand. A Turkish home textile brand can see in the report which terms US users emphasise, such as “organic cotton”, “does not shrink in the wash” or “hotel quality”, and rewrite its product data in that language. The second benefit of this use is being prepared when the report opens for Turkish queries. Teams that build the habit of reading the report, moving terms into the feed and measuring the effect in export markets can apply the same loop to the Turkish market much faster. Brands not covered by the report’s current scope can use this time to close basic gaps in their product data. According to information Google shared in the same announcement, merchants adopting core feed best practices see an average 5 percent increase in conversions the following month. If this foundation is already in place when the report arrives, changes in share of voice can be read far more meaningfully. [Selen Çetin](https://www.webtures.com/authors/selen-cetin/) Visibility Intelligence Specialist Published: 06 Oct 2026 Updated: 06 Oct 2026 [Add Webtures as a preferred source on Google](https://www.google.com/preferences/source?q=webtures.com) [Related service Generative Engine Optimization (GEO) Visibility inside SI answers Explore →](https://www.webtures.com/generative-engine-optimization-geo/) ## Articles related to Reading your brand share in Merchant Center AI performance insights [### Sell-side agentic commerce: when agents run the operation Gizem Sayan / 02 Oct 2026](https://www.webtures.com/insights/sell-side-agentic-commerce/) [### Agentic Commerce Readiness Report: how commerce infrastructure changes Webtures / 22 Sept 2026](https://www.webtures.com/insights/agentic-commerce-readiness-report/) [### How to Build a GEO Strategy for Cosmetics and Beauty Brands? Tufan Acar / 09 Sept 2026](https://www.webtures.com/insights/how-to-build-a-geo-strategy-for-cosmetics-and-beauty-brands/) [### GEO Predictions for 2027: Where Does SI Search Go Next Year? Selen Çetin / 03 Sept 2026](https://www.webtures.com/insights/geo-predictions-2027/) [### How to Adapt Content from Featured Snippet to SI Answers? Eren Kartav / 02 Sept 2026](https://www.webtures.com/insights/how-to-adapt-content-from-featured-snippet-to-si-answers/) [### What Is Dark SI Traffic? The Measurable and Hidden Side of SI-Driven Traffic Atiye Berika Ertaş / 28 Aug 2026](https://www.webtures.com/insights/what-is-dark-si-traffic-the-measurable-and-hidden-side-of-si-driven-traffic/)