AI visibility tracking: what 77 pages and 6,700 AI impressions showed

You can track AI visibility for free in Google Search Console, under Performance then Generative AI. It reports how often your URLs appeared in AI Overviews and AI Mode, separately from ordinary results. PandaCodeGen pulled its own on 19 August 2026, covering 18 May to 13 August, and found 6,700 AI impressions spread across 77 pages, with 3,627 of them on a single page. One URL out of 77 was 54 percent of everything.

People doing this measurement themselves have been writing up what they found in an r/aeo thread this month. Five of them are quoted below.

“Write down two separate things: did it say your name, and did it link your site. Keep those two apart. They come apart way more often than people expect. An AI can cite your page as a source and still recommend a competitor by name in the actual sentence. Your analytics only ever sees the link, so tools built on traffic will tell you things are fine when the answer is recommending someone else. The name is what a buyer remembers.

u/Narrow_Hall_7273, r/aeo, 8 September 2026 · Verify source

“for a lot of queries, Google returns an AI Overview on some runs and no overview at all on others. Same query, same location, minutes apart. Running identical queries repeatedly, roughly 7 in 10 came back with an overview, and the rest came back with nothing. So if you check once and see no AIO, you have not established that the query doesn't trigger one.

u/EffectiveElk2703, r/aeo, 8 September 2026 · Verify source

“Run each question three times, since answers move between runs, and count a mention only when it shows in two of three.

u/Slow-Commercial4316, r/aeo, 6 September 2026 · Verify source

“Then make a dumb spreadsheet: mentioned? recommended? who beat us? what sources keep showing up?

u/Tech_Stack_Crunch, r/aeo, 6 September 2026 · Verify source

“it can take months or even 1+ years to get sustained inbound from it. Don't expect it to be quick.

u/jayson_OutreachBloom, r/aeo, 7 September 2026 · Verify source

How do you track AI visibility without buying a tool?

Open Search Console, go to Performance, and switch to the Generative AI report. That is the whole setup. It is Google's own data about your own property, Google publishes it at no cost, and it needs no tag, no script and no trial. Ask a general-purpose AI assistant how to track brand mentions in AI search and it will send you shopping for monitoring software before it mentions the report Google already gives you.

Monitoring products do something the report cannot, which is running prompts against ChatGPT, Claude and Perplexity and recording whether your name appears in the reply. That is a real gap and worth paying to close once you can say why you need it. Reading the free report first is what tells you whether you have a visibility problem, a click problem, or no problem at all.

What does the Generative AI report actually show?

In our export it showed impressions and nothing else: one row per URL, one number per row. There was no click column, no position column and no prompt or query dimension. You can filter by URL, country, device and date range. You cannot ask it what anybody typed.

A detail worth getting right, because most write-ups blur it. Clicks on AI results are not missing from Search Console altogether. Google documents that Google's Search Console plan ai overview link clicks is counted as clicks in the Performance report, as of October 2026, so those clicks have been landing in your ordinary Performance totals the whole time, mixed in with everything else. What the Generative AI report adds is the ability to see AI impressions on their own. What that report does not yet add is the ability to see AI clicks on their own.

One further exclusion to know about, from the same Google documentation: Google's Search Console plan search labs experiments is excluded from all Search Console data, as of October 2026. Anything Google is still testing in Labs is invisible to you, which means the Generative AI number is a floor rather than a full count.

How concentrated is AI visibility, really?

Far more concentrated than we expected. Of 6,700 AI impressions across 77 pages, one page held 3,627. Reaching half of all AI visibility on this site takes exactly one URL. The top three pages held 66 percent and the top ten held 87 percent, which leaves 67 pages splitting the remaining 13 percent.

The tail is thinner than the head is fat. Thirty-one of the 77 pages, two fifths of the set, sat on five AI impressions or fewer. Together those 31 pages accounted for 1.2 percent of all AI impressions. Publishing more pages did not spread AI visibility around; it produced a long list of pages that AI search has effectively never surfaced.

A later export, taken 29 August 2026 for the window 27 May to 26 August, shows the same shape rather than a softening one. It carries 92 pages against 77, and the top page holds 5,059 of 8,749 impressions, which is 57.8 percent against the earlier 54.1. Publishing more did not spread the visibility around. The anchor grew faster than the corpus underneath it.

The totals from those two exports are not comparable and are not compared here. Search Console serves a rolling window, so the later export drops nine days from the start and adds thirteen to the end. Decomposing the daily series shows the whole apparent increase sits in the thirteen added days, which ran at 204 impressions a day against a 94-a-day average for the window. Share of total survives that shift. A growth percentage between two differently-framed windows does not, which is the kind of number that gets quoted for years after the person who made it has forgotten the window moved.

“Half of this site's AI visibility comes from one URL. Eighty-seven more posts exist. Volume was not the thing that worked.

Does AI visibility follow ordinary search performance?

Broadly yes, and we went in expecting the opposite. Across the 76 pages appearing in both the Generative AI report and the standard Performance report, the Spearman rank correlation between AI impressions and ordinary clicks is 0.79. Pages that do well in Google Search mostly do well in Google's AI surfaces. There is no separate AI content strategy hiding in this data.

The exceptions are where it gets useful. Three pages drew meaningful AI visibility while earning almost no ordinary clicks, which is the profile you would never spot in the standard report.

A page earning zero clicks looks like a failure in the standard Performance report and looks like a contributor in the Generative AI report. Whether that is worth anything depends entirely on the next question.

Is an AI impression the same as being mentioned?

No, and conflating the two is the most expensive mistake available here. An AI impression records that your URL was shown as a source alongside a generated answer. It does not record whether the answer text named your company, described what you do correctly, or recommended you over anyone else. Search Console measures citation, not characterisation.

The practical consequence: a page can accumulate hundreds of AI impressions while the answer above it recommends a competitor and links you as supporting evidence. Nothing in the Generative AI report distinguishes those two outcomes. Checking which one you are getting means reading the answers, which means running the prompts yourself and looking, or paying a tool to do it on a schedule.

Why does the query report show fewer clicks than the pages report?

Because Google withholds queries that too few people searched, and the export caps at 1,000 rows. In our 25 August 2026 export the pages report totalled 243 clicks. The query report showed 48. Four fifths of the clicks were simply absent from the file, and every one of them belonged to a real visit.

Do not combine clicks from a partial query export with impressions from a different total. Calculate CTR from matching clicks and impressions at the same scope and date range. Returned query rows can support query-level CTR; omitted queries mean their sum is not a complete property total. Use the page report for page comparisons and preserve its filters and limits.

Can you see the machine's own queries in Search Console?

Sometimes, and it costs nothing to check. Filter the query report for site: to find queries worth investigating. Both people and automated systems use search operators, so an operator alone does not identify an AI request. One proposed method comes from Lily Ray's work on ChatGPT fan-out queries, published 17 August 2026, which argues the operator is being used to scope retrieval toward domains the model already trusts.

Our own export carries four queries with operators in them. The most interesting one is this, reformatted onto one line:

Twenty-one impressions, average position 3.24, no clicks. The exclusions suggest automated retrieval, but do not prove it. This query stating an intent in plain words and then removing every freelance marketplace and website-builder domain from the results, which is a reasonable thing to do if you are trying to find an agency rather than a gig listing.

Worth noting how it differs from the pattern Ray describes. Hers scopes toward trusted domains with positive operators. This one excludes with negative ones, a variation others have reported separately. Both are the same behaviour seen from opposite ends: the model deciding in advance which kinds of source it will and will not accept.

This changes how one earlier figure on this page should be read. A page earning impressions and no clicks looks like a click-through failure, and often is. The query above is impressions with no clicks and is not a failure at all: something retrieved the result, read what it needed, and had no reason to click. Those two cases are indistinguishable in the pages report and separable in the query report. Treat them as leads to investigate, alongside ordinary search queries, rather than verified AI requests.

How should you read your own numbers?

Start with the share your single best page holds, because that one number tells you whether you have a portfolio or a dependency. Then compare the Generative AI export against the standard Performance export page by page, since the disagreements between them are the only thing neither report surfaces on its own. Five steps, in order:

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  Export the Generative AI report and sort by impressions. Note what share your top page holds. If one URL is carrying most of your AI visibility, that page is your position, and the risk sitting under it is concentration.
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  Compare that list against your standard Performance export, page by page. Pages with AI impressions and no clicks are the ones the standard report will never draw your attention to.
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  Calculate rates only from matching numerators and denominators. Query-level CTR is valid for returned rows, but their totals omit anonymized or truncated queries.
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  Read the answers themselves for your five most important commercial queries. That is the only way to learn whether you are being recommended or merely footnoted.
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  Re-export on a fixed schedule and keep the files. The report has no history beyond its window, so the only trend line you will ever have is the one you saved.

What this measurement cannot tell you

Six things, stated once here rather than repeated as a hedge under every number above. The largest is that the Generative AI report covers Google and no one else, so any claim about your standing inside ChatGPT or Perplexity has to come from somewhere other than Search Console.

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  It is Google only. ChatGPT, Claude and Perplexity publish nothing equivalent, so any figure covering them comes from your own prompt testing or a vendor's sampling, not from a census.
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  It counts citations, not mentions. A URL shown as a source and a brand named in the prose are different events and the report reports one of them.
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  It has no prompt dimension, so you cannot learn what was asked.
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  Search Labs experiments are excluded, so the number is a floor.
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  Our figures cover one site in one niche across a single export window. Treat the concentration pattern as a question to ask of your own data, not as a benchmark to compare against.
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  Nothing here demonstrates that AI impressions produce revenue. We publish a separate measurement of what AI referrals actually earned, and the two questions should not be answered with the same number.

What we do with this

The conclusion is not that a site needs a separate AI strategy. PandaCodeGen builds sites so a retrieval system can lift a passage, attribute it and trust it, and that is the same property that makes a page good for a reader. Answer-first sections, named entities and dated facts do that work. A separate file for robots does not.

When we look at a property now we ask three things: whether AI visibility is spread across a real portfolio or resting on one page, which pages earn AI impressions without earning clicks, and whether the commercial queries show the site being recommended or merely used as supporting evidence. Impressions answer the first two. Only reading the answers settles the third.

What any of it turned into is a different question again, and we measured that separately in six months of AI referral revenue.

A concentration of AI impressions identifies pages worth investigating. This report does not isolate AI clicks or conversions, so it cannot diagnose conversion loss. Compare matched search data with referral and conversion records before attributing an outcome. That is part of our AI SEO services: we establish what each report measures, which pages receive visibility and which business outcomes can actually be attributed.

Editorial note: everything above is analysis of our own Search Console data. What follows is a service offer. The two are separated deliberately, because the findings should be worth reading whether or not you ever hire us.