Tag: AI search analytics

This is the third piece in our series on how AI platforms decide who gets cited. The first looked at how much AI referral traffic ChatGPT controls. The second looked at how selective it is about which sources it trusts. This one asks the practical follow-up: if two of the biggest AI platforms disagree this much about sources, what does that do to the way you measure visibility?

The headline number is that only about 11% of domains are cited by both ChatGPT and Perplexity. It has been repeated in dozens of articles this year, usually with a sentence claiming that single-platform tracking leaves 89% of your visibility invisible. That last part goes further than the data supports. The 11% figure is real and worth acting on, but it is also easy to misread, and several of the studies stacked underneath it measure different things. Here is what each one actually found, and what it means for how you track your brand.

Where the 11% comes from

The figure appears in three related but distinct places, and they are not the same study repeated three times.

The first is a dataset of 680 million citations covering August 2024 to June 2025, analyzed by Profound and cited in Averi’s B2B SaaS benchmark report. Averi’s report states that only 11% of domains are cited by both ChatGPT and Perplexity. Worth noting: the 680 million analysis is Profound’s work, and Averi uses it as a supporting reference rather than presenting original research of its own. Several articles online attribute the analysis to Averi directly, which is a small but real attribution error.

The second is a Qwairy analysis of 118,000 AI responses collected between January and March 2026 across ChatGPT, Perplexity, Google AI Mode, and Claude, which Whitehat SEO cites in its own comparison. It found that only 11% of cited domains appeared across multiple platforms. That is a slightly different measurement from the first one. It looks across four platforms at once instead of comparing ChatGPT and Perplexity as a pair, so the matching 11% is a coincidence of two different methods, not one result confirmed twice.

The third is a Wellows study of 22.7 million citations across 1.15 million questions, covering January to June 2026. It approaches the same question from the opposite direction and reports that 89% of websites ChatGPT cited on a given question were never cited by Perplexity on that same question. That is essentially the mirror image of the 11% figure, measured at the website level, on identical questions.

So three datasets, three time windows, and two different definitions of overlap all point the same way: the two platforms draw on substantially different sets of sources. That agreement is the meaningful finding. The exact percentage matters less than the direction.

What the 11% does and does not mean

Now for the overreach. A low overlap between two platforms’ cited domains does not mean 89% of your potential visibility is hidden from you. Authority Tech, which curates and compares these studies, states explicitly that the figure does not imply that. There are three reasons.

First, the overlap is measured across all domains cited, not across your domain. Your brand could appear consistently on both platforms while the rest of the web fragments around you. The 11% describes the whole citation landscape, and your own footprint inside it is a separate question.

Second, Wellows itself is careful about this. Its authors describe the gap as a different candidate pool rather than a more unpredictable engine, and they point out that the number measures which sources answer a particular question, not which websites are permanently available to each platform.

Third, overlap depends heavily on how strictly you match. Wellows reports different results at website level, page level, and with different levels of address cleanup. A percentage that moves that much with the matching rule should be read as a range, not a fixed law.

The accurate version of the claim is narrower and still useful: if you only measure one platform, you are measuring a different slice of the web than the one your buyers see on the other. That alone is reason enough to change how you track.

A different 12% that gets mixed in

Ahrefs published a widely quoted 12% figure that often gets bundled into this conversation, and it deserves separating out. Ahrefs analyzed 15,000 long-tail queries in a study published on August 11, 2025, and found that only 12% of URLs cited by ChatGPT, Gemini, and Copilot also ranked in Google’s top 10 for the same prompt. The measurement compares AI citations with Google rankings. It does not compare one AI platform with another.

The Ahrefs data does contain a useful platform-level detail, though. Perplexity’s overlap with Google’s top 10 was 28.6%, far higher than ChatGPT at around 8%. So Perplexity leans on pages that also rank well in traditional search, while ChatGPT draws more heavily from pages that do not. Placed next to the 11% cross-platform figure, that goes a long way toward explaining why the two platforms disagree. They are retrieving from different places.

For anyone doing search engine optimization alongside AI visibility work, this is the important takeaway. Ranking well in Google helps you with Perplexity noticeably more than it helps you with ChatGPT. Treating them as one channel with one strategy will over-serve one and under-serve the other.

The same brand, very different results

Two more datasets show what this looks like at the brand level, and both are better evidence for multi-platform tracking than the 11% headline.

Superlines analyzed 34,234 AI responses across 10 platforms between January 14 and February 13, 2026, and reported a 615x gap in citation volume between the highest-citing platform, Grok at a 27.01% citation rate, and the lowest, Claude, at close to zero. The number is striking, but it needs context. It reflects how differently each platform handles linking out to commercial brand sites, which is partly a product design difference and not purely a measure of how much each platform likes any given brand.

Slate HQ published a 90-day study on March 30, 2026, tracking six B2B SaaS brands across ChatGPT, Perplexity, Gemini, Claude, Google AI Overview, and Google AI Mode, with more than 300,000 citation data points. Its central finding is that 76.3% of all citations went to domains that were neither the brand nor its direct competitors. Most of the visibility lives on third-party sources.

The per-platform breakdown Slate published for one email security client illustrates the spread. Brand-owned citation share was 10.2% on Google AI Mode, 10.0% on Google AI Overview, 9.1% on Claude, 6.9% on Gemini, 6.8% on Perplexity, and 4.5% on ChatGPT. Those are the numbers for one client, not an average across all six brands, and it would be wrong to say ChatGPT was the weakest platform for every company studied. But the spread within that single brand, more than double between the highest and lowest platform, makes the point clear. The same company can look strong on one platform and weak on another during the same 90 days.

Slate also found that Claude had the narrowest external source pool at 54% unidentified sources, while Perplexity cast the widest net at 67.7%. Different platforms are not just citing different pages. They are behaving differently in how broadly they search.

What to do with this

The practical response is not to panic about an invisible 89%. It is to stop treating AI visibility as a single number.

Track each platform separately. A blended score hides exactly the variation the studies above describe. At a minimum, report ChatGPT, Perplexity, Google AI Overviews, and Claude as separate lines, and watch each for movement independently. This is the foundation of any serious generative engine optimization program.

Identify which sources each platform trusts in your category. Since most citations go to third-party domains, your visibility depends on where you are mentioned as much as on what you publish. Check which review sites, directories, and community platforms each engine leans on for your topics, then look at whether you are present there.

Match your optimization to the platform. Because Perplexity correlates more strongly with Google rankings, traditional ranking work supports it. ChatGPT draws from a broader mix, so entity clarity, third-party mentions, and presence on the sources it favors carry more weight. This is where generative engine optimization and answer engine optimization diverge in practice, even though they are often discussed as one thing.

Set a baseline before changing anything. Record your citation presence per platform for a fixed set of prompts this week, then repeat monthly. Without a starting point, you cannot tell whether a change came from your work or from platform variability.

Treat every overlap statistic as a range. Different matching rules produce different percentages, and the sample sizes, time windows, and definitions vary. Use the studies to understand direction, then validate against your own prompts.

Where this leaves you

Only 11% of domains being cited by both platforms is a real signal, backed by three independent datasets using different methods. It does not mean 89% of your visibility is lost, and it is not the same as the Ahrefs 12% figure, which compares AI citations with Google rankings. What it does show is that ChatGPT and Perplexity behave like separate channels with separate source preferences, and that measurement built around one will miss what the other is doing. Track them separately, benchmark against a baseline, and treat the percentages as direction, not precision. That is the discipline answer engine optimization now demands.

Frequently Asked Questions

1. Is it true that only 11% of domains are cited by both ChatGPT and Perplexity?
Answer: Yes, that figure appears in several studies, including a 680 million citation dataset analyzed by Profound and a Qwairy analysis of 118,000 responses. Definitions differ slightly between studies, so treat 11% as an approximate indicator of low overlap, not an exact constant.

2. Does this mean 89% of my AI visibility is hidden if I only track one platform?
Answer: Not exactly. The 11% describes overlap across all cited domains, not your own brand. It does show that each platform draws on a different pool of sources, so single-platform tracking gives you an incomplete picture.

3. Is the Ahrefs 12% the same statistic?
Answer: No. Ahrefs found that only 12% of URLs cited by ChatGPT, Gemini, and Copilot also rank in Google’s top 10 for the same prompt. That compares AI citations with Google rankings, not one AI platform with another.

4. Which platform gives brands the highest citation share?
Answer: It depends on the brand and category. In Slate HQ’s example for one email security client, Google AI Mode and AI Overview were highest and ChatGPT was lowest. That is a single-client result and should not be generalized to every company.

5. What does the 615x citation gap mean?
Answer: Superlines found a 615x difference in citation volume between the highest platform, Grok, and the lowest, Claude, across 34,234 responses. It reflects how differently platforms link to commercial sites, so it shows platform behavior more than brand preference.

6. What should I track first?
Answer: Start with a fixed list of prompts your buyers actually ask, then record whether your brand is cited on ChatGPT, Perplexity, Google AI Overviews, and Claude separately. Repeat monthly and compare against that baseline.

If you want to see where your brand stands on each platform, not just one, that is exactly what we cover in a free AI Visibility Audit.

In August 2025, Google’s own John Mueller warned the SEO industry about something specific. Speaking about the growing pile of new acronyms, GEO, AIO, AEO, he warned that pushing new terminology too aggressively was often a signal of low quality tactics rather than genuine innovation. A month later, in September 2025, when a fake screenshot claimed Google had built a dedicated AI Overview filter inside Search Console, Mueller shut that down too, calling the screenshot fake and confirming no such feature existed.

Eleven months later, on 31 August 2026, Google built exactly that feature, for real, and rolled it out to every website on earth.

I want to walk through what actually changed, why the timing and the backstory matter more than the feature itself, and exactly how to check this on your own site.

The rumour that turned out to be a preview of the future

The story is worth telling properly, because it says something about how much pent up demand existed for this.

On 15 September 2025, a user holding Platinum Product Expert status in Google’s own Search Console help forums, Adrian Coutin, posted that Google had integrated data for AI-generated search features directly into Search Console’s Performance reports. The post included a fabricated screenshot showing a new Search Appearance filter specifically for AI Overview data. It spread fast, because it was exactly what site owners had been asking for.

Mueller responded on LinkedIn within hours. “There’s no filter like this in Search Console, and the screenshot itself is fake,” he wrote. Coutin deleted his original post and apologised for the error.

For the following year, Google’s official position stayed consistent, AI Overview and AI Mode data was folded into the standard performance numbers, with no way to separate it out, and no committed timeline to change that. Multiple SEO guides published through late 2025 and into early 2026 describe workarounds involving third party tools precisely because Google offered nothing native.

Then, in June 2026, Google quietly began testing a real version of exactly the feature Coutin had faked, on a limited subset of properties. On 31 August, that testing phase ended, and the feature went live everywhere.

What actually shipped

Google confirmed the global rollout on its own Search Central blog, describing the new reports as dedicated views of impressions specifically within generative AI features on Search, covering AI Overviews and AI Mode, as well as the generative AI features that now appear inside Discover.

Search Engine Journal’s coverage of the global launch adds a detail worth knowing before you go looking for it. Not every property has access yet, and sites with a low volume of AI impressions may not show meaningful data in the report even where it is available. If you check and see very little, that is not necessarily a sign the report is broken. It may simply reflect where your content currently sits in AI systems.

The report breaks impressions down by page, by country, and by date. What it does not include, and this is the detail every source I checked agrees on without exception, is clicks, click through rate, or the specific queries that triggered an appearance. You can see that a page from your site showed up inside an AI generated answer. You cannot see what someone typed to get that answer, and you cannot see whether they clicked through to you afterward.

The report is best understood as a record of where you showed up, not a measure of what that appearance actually earned you in traffic or business.

Google also shipped an opt out control alongside the reporting, letting site owners remove themselves from these AI features entirely. Google has stated that using this toggle does not affect a site’s ranking anywhere else in standard Search results, which matters, because it means the choice to opt out is a genuine preference rather than a trade-off against traditional visibility.

Why the backstory matters more than the button

I keep returning to the Mueller timeline because it tells you something the feature announcement alone does not.

In August 2025, Google’s own search advocate was publicly wary of the entire AI visibility conversation, treating the proliferation of GEO and AEO terminology as a likely signal of low quality hype rather than a legitimate new discipline. A month later, Google was actively denying it had built any tooling to support that conversation.

Less than a year on, Google built the tooling anyway, at a global scale, unprompted by any specific competitive pressure that forced its hand. That sequence is a stronger signal than the launch blog post itself. It suggests the internal case for treating AI visibility as a distinct, measurable category became undeniable even to a company that was publicly skeptical of the framing not long before.

For anyone running SEO or GEO work for a client, that timeline is useful ammunition. The scepticism you may have encountered from more traditional stakeholders, the idea that AI visibility is a marketing buzzword rather than something worth the budget, gets harder to sustain once the platform itself has built a dedicated reporting surface for exactly that.

The data that explains why Google finally built this

Two independent data points, unrelated to this launch, explain the pressure Google was likely responding to.

Semrush’s AI Visibility Index, tracking brand mentions across Google’s AI Mode over several thousand prompts, found a 4 percent drop in mention share between August and October last year, while the diversity of sources being cited across the same period rose 13 percent. Visibility was getting harder to hold onto and more competitive at the same time, with no native way for an affected business to even confirm it was happening.

BrightEdge’s industry wide data adds the commercial pressure point. Search impressions are up 49 percent year over year, while click through rate on those impressions is down 30 percent over the same period. Businesses have been watching their visibility numbers climb while their actual traffic stalls or falls, with no first party data source able to explain why. That is precisely the gap this report is built to close, even if only partially.

How to actually find and use this on your own site

Coverage of exactly where this sits inside the Search Console interface is not fully consistent across sources I checked, some describe it as a dedicated left navigation item, others as a filter within the existing Performance report. Rather than send you hunting for one specific click path that may not match what you see, the reliable approach is this. Open your Performance report inside Search Console for the property in question, and look for a Generative AI or AI features option, either as a separate section or as a filter on your existing search appearance data. If it is not visible yet, that is consistent with Google’s own rollout note that access is expanding property by property rather than appearing identically for everyone on day one.

Once you find it, compare the AI impression volume against your total Web impressions for the same period. If AI generated impressions represent a meaningful share of your total visibility, and your click through rate has been falling without a ranking drop to explain it, that gap is very likely hiding inside exactly this data. This is the same pattern the BrightEdge numbers describe industry wide, positions can hold while clicks fall, because an increasing share of answers are being delivered before anyone reaches your listing.

If the number is small or close to zero, treat that as informative in a different way. It likely means your content is not currently being retrieved for the kinds of questions that trigger these AI features in your category, which is a different and in some ways more urgent problem than a visibility measurement gap.

What not to do with this data yet

Do not draw conclusions from a single week. This is newly global infrastructure, and Google’s own historical pattern with new reporting features is that data takes time to stabilise as more properties gain access and reporting pipelines mature.

The useful read is a trend over four to eight weeks, not a snapshot. Is your share of AI impressions climbing, flat, or falling relative to your total visibility over that window. That trajectory tells you far more than any single day’s number, particularly while the feature is still rolling out unevenly across different sites.

Frequently asked questions

1. Does this show me if ChatGPT or Perplexity cite my site?
Answer: No. This report is scoped entirely to Google’s own AI features, AI Overviews, AI Mode, and Discover’s generative surfaces. It has no visibility into any AI platform outside Google’s own products. Measuring citation inside ChatGPT, Claude, Gemini, or Perplexity still requires testing those platforms directly, since none of them currently offer a first party reporting tool of their own.

2. Does a high AI impression count mean I am getting more traffic?
Answer: Not necessarily, and this is the central limitation to keep in mind. The report measures impressions only. BrightEdge’s industry data shows click through rate falling even as impressions rise broadly, so a strong impression number does not guarantee a proportional lift in actual visits.

3. Can I see which search queries triggered my AI impressions?
Answer: No, and every source covering this launch agrees on that point. Query level detail is one of the more consistently requested features Google has not shipped, alongside click data.

4. Should I use the opt out toggle?
Answer: For most businesses, no. Google has confirmed opting out does not improve or protect your standing in standard Search results, so opting out only removes a visibility channel without gaining you anything in return. It exists mainly for edge cases such as publishers protecting content behind a specific business model, not for typical service or B2B businesses trying to be found.

5. Why did it take Google so long to build this, given the September 2025 rumour showed clear demand?
Answer: Google’s public position throughout that period was that AI Overview data belonged inside standard performance reporting rather than a separate view. The shift to building a dedicated report suggests the internal case changed, likely under the same pressure reflected in the Semrush and BrightEdge data, impressions climbing, clicks falling, and no way for site owners to see why.

If you want visibility that goes further than what Google’s own tools can show, including whether ChatGPT, Claude, Gemini, and Perplexity are actually citing you, that is exactly what we check in a free AI Visibility Audit.