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Chaudhary",[451],{"type":27,"image":452,"mobileImage":456},[453],{"src":454,"alt":9,"width":455,"height":455},"https:\u002F\u002Fd191k2rrohvvg6.cloudfront.net\u002Fimages\u002F1730657296846.jpeg",800,[],"Head of Visibility and VP-Business","\u003Cp>Suraj is the Head of Visibility and VP-Business at Pixis. An ex-Bain consultant with experience across growth, strategy, and operations, he is a thought leader AI search visibility and helps businesses understand how discoverability is changing in the age of generative search. Having scaled Visibility to $3M ARR in just 2 months is a testimony to his understanding of the space!\u003C\u002Fp>",{"url":460},"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fchaudharysuraj\u002F?skipRedirect=true",[],{"title":463,"description":464,"advanced":465,"keywords":468,"social":469},"How to Find AI Queries in Google Search Console | Pixis","Google Search Console can inform your AI prompt strategy. Learn to find useful questions, interpret the evidence, and decide what content deserves attention.",{"canonical":466,"robots":467},"",[],[],{"facebook":470,"twitter":471},{"description":464,"title":463},{"description":464,"title":463},[473],{"type":27,"image":474,"mobileImage":479},[475],{"src":476,"alt":9,"width":477,"height":478},"https:\u002F\u002Fd191k2rrohvvg6.cloudfront.net\u002Fimages\u002Fimage-2026-09-30T195558.103.png",1920,1360,[],[481,484,487],{"title":482,"slug":483},"AI","ai",{"title":485,"slug":486},"Performance Marketing","performance-marketing",{"title":488,"slug":489},"Pixis Visibility","pixis-visibility",true,[492],{"blocks":493},[494],{"type":495,"textBlock":496},"textBlock_Entry","\u003Cp>A marketer opens Search Console and finds a query that reads like a conversation: “which advertising platform works for a small team with no designer?” It is tempting to label it an AI prompt and count the associated impressions as evidence of AI visibility.\u003C\u002Fp>\u003Cp>The query cannot tell you that. What it does reveal is a buying constraint your content may have overlooked. The person is evaluating software through the limits of their team. A feature list alone may not answer the question.\u003C\u002Fp>\u003Cp>That is where Google Search Console becomes useful for AI search strategy. Its query data can help you choose better questions to investigate, even when it cannot tell you where those questions originated. The opportunity is to let customer language change your content decisions without asking the data to prove more than it can.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Key Takeaways\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cul>\u003Cli>Regex filters identify query patterns. They do not establish that a search came from an AI assistant or earned an AI citation.\u003C\u002Fli>\u003Cli>Google’s dedicated generative AI reports provide page-level visibility information, but do not supply the query breakdown behind those appearances.\u003C\u002Fli>\u003Cli>Detailed queries can expose the conditions under which a buyer would choose your product. Preserve those conditions when building a prompt library.\u003C\u002Fli>\u003Cli>GSC reflects searches where your site already appeared. Add questions from sales conversations and customer research to investigate gaps outside that existing visibility.\u003C\u002Fli>\u003Cli>Use each finding to make a specific decision. Sometimes the right response is to improve an existing page; sometimes it is to investigate further before publishing anything.\u003C\u002Fli>\u003C\u002Ful>\u003Ch2>\u003Cstrong>The Query Is Valuable Before You Know Its Origin\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>Consider the difference between “AI advertising software” and “AI advertising software for a team without a designer.” The second query gives the marketing team a much more demanding job.\u003C\u002Fp>\u003Cp>The reader may need to understand what they can produce without design support and how much review the output requires. If your page simply repeats that the product saves time, it leaves the central concern unanswered.\u003C\u002Fp>\u003Cp>That remains true whether the question was typed into conventional Google Search or an AI interface. Trying to classify its origin can become a distraction from the need it expresses.\u003C\u002Fp>\u003Cp>This is the judgment content teams should bring to GSC. Look for details that would change the answer: a limited budget, an existing platform the buyer cannot replace, or an approval process that makes a seemingly simple workflow difficult. Those details help you distinguish a useful page from a generic category overview.\u003C\u002Fp>\u003Cp>They also give you more purposeful prompts to test. Asking an engine to recommend software for a small team without design support is a different investigation from asking it to list the best advertising platforms.\u003C\u002Fp>\u003Ch2>\u003Cstrong>What Google’s AI Reporting Actually Adds\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>Google\u003Ca href=\"https:\u002F\u002Fdevelopers.google.com\u002Fsearch\u002Fblog\u002F2026\u002F06\u002Fgen-ai-performance-reports\"> introduced Search Generative AI performance reports in June 2026\u003C\u002Fa>. An update to the announcement states that availability expanded worldwide on August 31. The reports provide impressions and page-level information, with country and date breakdowns and device information for Search.\u003C\u002Fp>\u003Cp>They do not provide the query dimension needed to connect a specific question to a particular AI appearance.\u003C\u002Fp>\u003Cp>Google also documents that\u003Ca href=\"https:\u002F\u002Fsupport.google.com\u002Fwebmasters\u002Fanswer\u002F7042828\"> AI Mode follow-up questions count as new queries\u003C\u002Fa>. That explains why conversational fragments are worth examining. It does not mean every “yes please” in a query export can be identified as an AI Mode interaction.\u003C\u002Fp>\u003Cp>Use the reports for the questions they can answer. The dedicated report can show a page appearing in generative AI features. The standard query report can reveal language associated with your search visibility. Finding the same page in both is a reason to investigate, not proof that a particular query produced its AI impression.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Four Filters That Can Improve Your Questions\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>The filters below are research aids. They create manageable groups of queries to review; none is an AI-origin detector.\u003C\u002Fp>\u003Cp>In Search Console, open \u003Cstrong>Performance → Search results\u003C\u002Fstrong>, choose a date range, and select \u003Cstrong>Add filter → Query → Custom (regex)\u003C\u002Fstrong>. Paste a pattern with \u003Cstrong>Matches regex\u003C\u002Fstrong> selected. Google’s\u003Ca href=\"https:\u002F\u002Fsupport.google.com\u002Fwebmasters\u002Fanswer\u002F17011165?hl=en\"> filtering documentation\u003C\u002Fa> confirms that GSC uses RE2 and that regex matching is case-insensitive by default.\u003C\u002Fp>\u003Ch3>\u003Cstrong>1. Find Queries With More Context\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>This pattern matches ten or more whitespace-separated tokens:\u003C\u002Fp>\u003Cp>^(?:\\S+\\s+){9,}\\S+$\u003C\u002Fp>\u003Cp>Length is a convenient way to find specificity, although a long query is not automatically valuable. Read for a condition that changes what the searcher needs.\u003C\u002Fp>\u003Cp>For example, “how do I compare ad performance across stores with different budgets” contains a measurement problem that a general advertising guide may never address. Keep the condition about different budgets when turning it into a test prompt. Removing it would remove much of the question’s value.\u003C\u002Fp>\u003Cp>If the results are sparse, change {9,} to {7,} to include queries with eight or more tokens.\u003C\u002Fp>\u003Ch3>\u003Cstrong>2. Find Evaluation Questions\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>^(how|what|why|which|who|when|where|is|are|can|does|do|should)\\b|\\b(best|vs|versus|alternatives?|compared? to)\\b\u003C\u002Fp>\u003Cp>This will return ordinary search queries as well as conversational ones. Its purpose is to uncover questions your team should be able to answer convincingly.\u003C\u002Fp>\u003Cp>Look beyond the obvious comparison-page opportunity. A recurring “can” question may reveal uncertainty about a capability. A “which” question may expose a choice your current content does not help readers make.\u003C\u002Fp>\u003Cp>Before commissioning a new article, inspect the page already earning impressions. It may need a clearer answer or better evidence rather than a companion post competing for the same intent.\u003C\u002Fp>\u003Ch3>\u003Cstrong>3. Find Requests for Help With a Task\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>^(please\\s+)?(write|draft|generate|summarize|rewrite|translate|explain|compare|suggest|estimate|plan|find)\\b|^(give|show|tell)\\s+me\\b|^can\\s+you\\b\u003C\u002Fp>\u003Cp>These queries can reveal the work people want help completing. “Compare” may call for a decision framework; “estimate” may point to a calculation the reader cannot make from the information currently available.\u003C\u002Fp>\u003Cp>The verb is only a starting point. A request to write a social post does not automatically justify another article about social media. Read the full request, establish its relevance to your audience, and decide whether you have something useful to contribute.\u003C\u002Fp>\u003Ch3>\u003Cstrong>4. Inspect Tool Names and Search Operators Separately\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>site:|\\b(chatgpt|perplexity|claude|copilot|gemini|deepseek|grok)\\b\u003C\u002Fp>\u003Cp>This filter gathers two categories that need different interpretations. Tool-name queries may show people researching assistants. They do not prove that those people use the named tools. A site: query shows an operator in the search text, not whether a person or agent submitted it.\u003C\u002Fp>\u003Cp>Use a property-relevant example such as site:yourdomain.com pricing when explaining the latter. Review ambiguous names manually: “Gemini” and “Claude” can refer to subjects unrelated to AI.\u003C\u002Fp>\u003Cp>This group is useful when it exposes confusion about your content or product. It is less useful as a basis for deciding which AI engines your whole audience prefers.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Build a Research Set Without Inflating the Numbers\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>Export the matching queries and preserve the original wording. Add a field for the question or constraint you think each one expresses.\u003C\u002Fp>\u003Cp>The filters overlap. A long comparison query naming ChatGPT might appear in several exports. Deduplicate the records before calculating totals, retaining the matching filter names as labels. Otherwise, the same impressions can be counted more than once.\u003C\u002Fp>\u003Cp>Keep the reporting conditions consistent when comparing periods. A rise in filtered impressions means your site appeared more often for that query group. It could reflect better visibility or changing demand; the increase alone does not distinguish the two.\u003C\u002Fp>\u003Cp>Likewise, low CTR does not prove an AI answer satisfied the searcher. Inspect the result context and the page’s fit before diagnosing the cause.\u003C\u002Fp>\u003Cp>The goal is to leave this exercise with a set of questions worth working on. A larger spreadsheet is not an outcome in itself.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Your Existing Visibility Is a Starting Point With a Blind Spot\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>GSC can only show you a slice of the market. Your query data is shaped by where your site already appears, and some queries are withheld for privacy. Even the\u003Ca href=\"https:\u002F\u002Fdevelopers.google.com\u002Fwebmaster-tools\u002Fv1\u002Fsearchanalytics\u002Fquery\"> Search Analytics API\u003C\u002Fa> does not guarantee that every data row will be returned.\u003C\u002Fp>\u003Cp>If your business has never published credible information about a particular use case, that use case may be missing from the export. Treating GSC as your entire prompt strategy would carry that absence into your monitoring program.\u003C\u002Fp>\u003Cp>Add questions from sales calls and customer research. Pay attention to objections that recur before a purchase, especially when your content team has assumed the answer is obvious.\u003C\u002Fp>\u003Cp>Suppose prospects repeatedly ask whether they need an agency to use your product. Even if the question produces no visible GSC rows, it may deserve testing across AI engines. The absence of a recorded query does not make the concern unimportant.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Let the Finding Determine the Content Decision\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>Imagine a hypothetical brand that finds several queries about using its software without specialist support. The relevant page earns impressions, but says little about onboarding.\u003C\u002Fp>\u003Cp>The team tests a few carefully worded versions of the question in AI engines. Some answers describe the product as requiring substantial technical expertise. The team then checks that description against the actual implementation requirements.\u003C\u002Fp>\u003Cp>If the description is accurate, the marketing task is to explain those requirements clearly. If it is outdated, the team can investigate the cited sources and make current evidence easier to find. The useful intervention might be a detailed onboarding page or a correction to an external review.\u003C\u002Fp>\u003Cp>Publishing a new “best tools” article would not necessarily address the problem.\u003C\u002Fp>\u003Cp>This is also why a missing brand mention should start an investigation rather than trigger an automatic brief. The answer may serve a use case your product does not fit. Where the issue is an inaccurate description, our guide to\u003Ca href=\"https:\u002F\u002Fpixis.ai\u002Fblog\u002Fthe-ai-narrative-gap-the-story-you-tell-vs-what-ai-says\u002F\"> the AI narrative gap\u003C\u002Fa> explains how to benchmark it against verified facts.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Give the Prompt Library an Owner\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>A prompt library becomes useful when someone is responsible for reviewing what changes and deciding whether the change matters.\u003C\u002Fp>\u003Cp>Keep the original GSC query beside the prompt you test. Rewriting a fragment into a complete question is often necessary, but adding a budget or audience assumption can change the meaning. Record those decisions.\u003C\u002Fp>\u003Cp>For repeat checks, keep wording and collection conditions as consistent as practical. Separate a brand mention from a link to your website. Inspect third-party citations where they help explain an answer, and record the evidence behind any content change you commission.\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fpixis.ai\u002Fproducts\u002Fpixis-visibility\u002F\">Pixis Visibility\u003C\u002Fa> can support the monitoring work by helping teams examine their brand’s presence in AI answers and compare it with competitors. GSC supplies questions grounded in observed Google searches; a visibility platform helps you investigate how your selected questions are answered elsewhere.\u003C\u002Fp>\u003Cp>The team still owns the important judgment: whether the answer is accurate, whether your brand belongs in the consideration set, and what action the evidence supports.\u003C\u002Fp>\u003Ch2>\u003Cstrong>Start With the Question Your Current Page Avoids\u003C\u002Fstrong>\u003C\u002Fh2>\u003Cp>There is a useful test for the next GSC export: find a query whose wording makes your current page feel incomplete.\u003C\u002Fp>\u003Cp>Read the page as that searcher. Look for the answer to their specific concern. If it is missing, establish what information would help them decide and whether your business can substantiate it.\u003C\u002Fp>\u003Cp>That is a concrete way to improve content while building a more thoughtful AI monitoring program. You do not need to prove that a query came from a chatbot to recognize that it deserves a better answer.\u003C\u002Fp>\u003Ch2>\u003Cstrong>FAQs\u003C\u002Fstrong>\u003C\u002Fh2>\u003Ch3>\u003Cstrong>Can Google Search Console show me ChatGPT prompts?\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>It is not a dependable source of ChatGPT conversation data. Treat GSC as a source of Google search queries, some of which may be useful candidates for separate AI testing. Query wording alone does not identify the system that generated or received it.\u003C\u002Fp>\u003Ch3>\u003Cstrong>Do regex filters isolate AI Mode queries?\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>No. They match text patterns. Long questions and conversational replies can be worth investigating, but a match does not confirm AI Mode origin or an AI citation.\u003C\u002Fp>\u003Ch3>\u003Cstrong>What does Google’s generative AI report show?\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>Google’s announcement describes impressions and page-level visibility in generative AI features, with additional breakdowns such as country and date. It does not provide the query-level attribution needed to connect a particular question to a page’s AI appearance.\u003C\u002Fp>\u003Ch3>\u003Cstrong>Should every useful query become a new article?\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>No. First inspect your existing coverage. The right response may be a clearer explanation on a product page, a substantive update to an article, or further research. Create a separate page when the intent warrants one and you can add meaningful information.\u003C\u002Fp>\u003Ch3>\u003Cstrong>How should I choose which prompts to track?\u003C\u002Fstrong>\u003C\u002Fh3>\u003Cp>Start with questions that matter to a customer decision and that your team can act on. Include questions from outside GSC so the library is not limited to areas where you already have search visibility. Review the set as your product and customer needs change.\u003C\u002Fp>\u003Cp> \u003C\u002Fp>",[],{"blogBanner":499},{"bannerIcon":500,"bannerBrandName":505,"bannerHeading":510,"bannerCta1Text":511,"bannerCta1Url":93,"bannerCta2Text":512,"bannerCta2Url":277},[501],{"url":502,"title":503,"width":504,"height":504},"https:\u002F\u002Fd191k2rrohvvg6.cloudfront.net\u002Fimages\u002Fv-logo.svg","V logo",78,[506],{"url":507,"title":508,"width":509,"height":60},"https:\u002F\u002Fd191k2rrohvvg6.cloudfront.net\u002Fimages\u002Fvisibility-logo.svg","Visibility logo",191,"Increase your visibility on Google and AI search","Book a demo","Signup for free",1790847886332]