Every claim below circulates widely in writing about generative engine optimisation. We went to the
primary source for each one and tried to reproduce the number. The grade records what happened. Where
we failed to reproduce something, we say so rather than repeat it, and where we got something wrong
ourselves, it is in corrections.
19 claims · last checked 2026-07-10 ·
how we grade
The scale
VERIFIED
We fetched the primary source ourselves and the numbers reproduced.
DIRECTIONAL
A real, named source exists, but it is single-sourced or only partly reproducible.
UNREPRODUCED
A source is cited for the number, but we could not surface that number from it.
UNTRACEABLE
The number circulates widely with no locatable primary source.
MISLEADING
The source is real, but the claim misrepresents what it measured.
REFUTED
A named primary source directly contradicts the claim.
“Brands hold a ranking position inside AI answers, and you can track it.”
Measured and contradicted. There is under a 1-in-100 chance of even the same list twice.
What the source actually says
Same list of brands: under 1 in 100. Same list in the same order: roughly 1 in 1,000. Runners used default, personalised settings rather than pinned temperature, deliberately reflecting real-world conditions. The direct implication is that a single 'AI ranking position' is not a stable quantity.
“there's a <1 in 100 chance that ChatGPT or Google's AI, if asked 100X, will give you the same list of brands in any two responses”
“AI visibility is one number, and a brand visible in ChatGPT is visible across AI search.”
Only 2.37% of cited URLs appear in all three major engines. 91.07% appear in exactly one.
What the source actually says
Citations are overwhelmingly fragmented by engine: 2.37% universal overlap, 91.07% single-engine. The commercial consequence is that any tool reporting one blended 'AI Visibility %' across engines is averaging three near-disjoint populations.
“only 2.37% of cited URLs show up across all 3 engines”
3,700,000 URL citations from a 20,000-prompt random sample, across ChatGPT, Perplexity and Google AI Overviews, Q3 2025 to Q1 2026, from Omnia's live prompt monitoring pool
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the article and confirmed both figures and the dataset. One caveat the secondary coverage consistently omits, which we found on the source: the prompt pool is Europe-weighted and Spain-heavy, plus UK, Nordic and EU markets. It is not a global or US-representative sample. Treat the exact percentages as European.
“Adding schema markup increases how often AI assistants cite your pages.”
The publisher that sells rank tools ran the experiment and found no uplift on any platform.
What the source actually says
Across the platforms measured, the change in citations after adding schema was statistically indistinguishable from zero: Google AI Mode +2.4%, ChatGPT +2.2%, and Google AI Overviews actually -4.6% (a small but significant decline). The pages studied were already receiving AI citations, so the experiment tests whether schema lifts already-cited pages, not whether it helps undiscovered ones.
“Adding schema produced no major uplift in citations on any platform.”
1,885 URLs that added JSON-LD, against 4,000 matched controls, Aug 2025 to Mar 2026
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the article and confirmed the conclusion, the per-platform figures, the sample of 1,885 treated pages against 4,000 controls, the dates and the authors. Ahrefs sells rank tracking rather than schema tooling, so if anything the incentive ran towards a tidy positive result; it did not find one.
“Long-form content (2,000+ words) gets cited more often by AI.”
Word count and citation are essentially uncorrelated, and most cited pages are short.
What the source actually says
There is almost no relationship between how long a page is and whether it is cited: Spearman 0.04. In fact 53.4% of pages cited by AI Overviews are under 1,000 words, and only 16.0% are over 2,000. The idea that long-form mega-guides dominate AI citation is contradicted by the distribution.
“The Spearman correlation between word count and citation position is 0.04, essentially zero.”
560,346 AI Overviews, 1,677,876 cited URLs, 174,048 pages with valid word counts
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the article and confirmed the 0.04 correlation, the 53.4% under-1,000-words figure, the sample sizes and the date. Scope caveat worth carrying: this dataset is Google AI Overviews only, not ChatGPT or Perplexity.
“Generative engine optimisation boosts a brand's visibility in AI answers by up to 40%.”
The paper says this. The paper is measuring a benchmark, not ChatGPT.
What the source actually says
The uplift is measured on GEO-bench, a research benchmark the authors introduce in the same paper, using a 'visibility' metric derived from how much of a generated response is attributable to a given source. It is a controlled lab result. It is not a measurement of citation behaviour on ChatGPT, Perplexity, Claude or Google AI Overviews, and the paper does not claim it is. Almost every marketing page that repeats the 40% omits this.
“GEO can boost visibility by up to 40% in generative engine responses.”
2023-11-16, last revised 2024-06-28 (v3). Accepted to KDD 2024.
Sample
GEO-bench, a benchmark of diverse user queries across multiple domains
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the arXiv abstract and confirmed the sentence verbatim, and confirmed GEO-bench is introduced by the same paper. The abstract page does not state GEO-bench's query count, so we do not publish one. Figures of '~10,000 queries' circulate; we could not confirm that number from the abstract and have not read the full PDF.
“If you rank in Google's organic top 10, you will be cited in AI Overviews.”
It was mostly true a year ago. It is now true of well under half of citations.
What the source actually says
The share of AI Overview citations that also appear in the SERP's first 10 blocks fell from roughly 76% in July 2025 to 37.9% in January 2026. Restricted to organic results only, the figure is 37.10%. The authors attribute the shift to AI Overviews drawing more on the SERPs of fan-out sub-queries than on the original query's SERP.
“Google is selecting far fewer pages straight from the original SERP (~76% in July 2025 vs. ~38% today).”
“AI assistants return the same brand list less than 0.1% of the time.”
Off by a factor of ten. 0.1% is the figure for the same list in the same ORDER.
What the source actually says
Two distinct figures exist and are routinely conflated. List membership repeats at under 1 in 100 (under 1%). List ordering repeats at roughly 1 in 1,000 (about 0.1%). Any page citing '0.1% chance of the same list' has swapped one for the other.
“when it comes to ordering, AI tool responses are so random that it's more like 1 in 1,000 runs before you'd see two lists in the same order”
We reproduced this from the primary source.checked 2026-07-10
We caught this because we made the error ourselves. During the research behind this site we were handed the conflated version and repeated it before checking the primary source. The correction is logged at /corrections/.
True on some engines, false on the biggest one. It flips by platform.
What the source actually says
The most-cited domain depends entirely on which engine you mean. On ChatGPT the top source is Wikipedia at 7.8%, with Reddit second at 1.8%. On Google AI Overviews and Perplexity, Reddit is first (2.2% and 6.6%). A blanket 'Reddit is most-cited' is true for two engines and false for ChatGPT, the largest.
“Reddit emerges as the leading source for both Google AI Overviews (2.2%) and Perplexity (6.6%).”
680,000,000 citations across ChatGPT, Google AI Overviews and Perplexity
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the Profound analysis and confirmed the per-platform leaders and their percentages, and the 680M-citation dataset. The claim is graded MISLEADING because it states as a universal fact something that is platform-specific and reverses across platforms. Profound sells AI visibility tracking.
“Adobe (or Salesforce) found that 58% of consumers now use AI instead of search engines for product recommendations.”
The 58% is real, but it is Capgemini's, not Adobe's, and it is a survey of what people say they do.
What the source actually says
The 58% figure comes from Capgemini, not Adobe or Salesforce, and it is a self-reported survey of stated behaviour (up from 25% the year before), not a measurement of actual traffic. Adobe did publish a 58% figure in the same period, but it is about consumers' willingness to share personal information for convenience, an unrelated question, which is the likely root of the misattribution.
“More than half (58%) have replaced traditional search engines with Gen AI tools as their go-to for product/service recommendations.”
12,000 consumers across 12 countries, surveyed October to November 2024
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the Capgemini release and confirmed the 58% wording, the up-from-25% comparison, the 12,000-consumer sample, the countries and the dates. Graded MISLEADING because the claim as circulated attributes the number to the wrong company and presents a stated-preference survey as measured behaviour. The underlying Capgemini number is real.
“Adding an llms.txt file improves your chances of being cited by AI assistants.”
No study we can find demonstrates it. Google's John Mueller says no AI service has confirmed using the file.
What the source actually says
Nothing traceable supports the positive claim. No controlled study, no server-log analysis and no vendor dataset that we could locate shows llms.txt increasing citation. The evidence that exists points the other way, though see the companion claim on this page, because that counter-evidence has its own problems.
Source
unattributed; circulates across vendor blogs and SEO guides
Published
unknown
Sample
none disclosed
Reproduction
No primary source exists to reproduce.checked 2026-07-10
We looked for a study supporting the claim and found none. We publish an llms.txt file ourselves, to describe the site rather than because we believe it changes anything. If you can produce a controlled study either way, we will grade it.
“YouTube mentions correlate with AI visibility at r = 0.737.”
We cannot find the study. The Semrush study that does exist says it did not test this.
What the source actually says
Nothing, as far as we can establish. The Semrush study we could locate (11,882 prompts, 337,785 URLs, published 14 January 2026) explicitly states that it did not test YouTube or backlink correlations. The 0.737 figure appears across multiple vendor blogs with no primary link.
Source
attributed to a 'Semrush AI Visibility Index' of 126 million prompts
Published
unknown
Sample
claimed 126,000,000 prompts
Reproduction
No primary source exists to reproduce.checked 2026-07-10
No primary source located. Until someone produces the underlying report, treat this number as unsupported. If you have a primary link, send it and we will regrade in public.
“A 100-word Reddit comment gets cited by AI 12 times more often than a 2,000-word guide.”
A suspiciously precise number with no methodology anywhere behind it.
What the source actually says
Nothing traceable. That Reddit and other user-generated content carry meaningful AI citation share is separately supported, notably by Profound's citation dataset. The specific '12x versus a 2,000-word guide' comparison is not, and reads as marketing copy rather than a measurement.
Source
unattributed; circulates across vendor blogs
Published
unknown
Sample
none disclosed
Reproduction
No primary source exists to reproduce.checked 2026-07-10
No primary source located. Note the shape of this claim: an exact multiplier, two arbitrary word counts, no sample, no engine named, no date. That shape is the tell.
“The GEO market grows from $848M in 2025 to $33.7B by 2034, a 50.5% CAGR.”
Repeated across dozens of blogs. We could not trace it to any named research firm.
What the source actually says
Nothing we could verify. Separate analyst projections for this category do exist and are also estimates rather than measurements. Capital flows are checkable and are a better signal: Profound raised a $96M Series C at a $1B valuation in February 2026.
Source
unattributed; circulates across secondary blogs
Published
unknown
Sample
none disclosed
Reproduction
No primary source exists to reproduce.checked 2026-07-10
No primary source located. Market-size projections in emerging categories are, by construction, estimates. Do not use one as evidence that a tactic works.
“AI crawlers requested /llms.txt in only 0.1% of hits: 84 out of more than 62,100.”
We believe the direction. We could not get these numbers off the page they are attributed to.
What the source actually says
The article argues that marketers misunderstand llms.txt and that AI bots largely ignore it. When we fetched the page, it did not yield the sample size, the date range, or the 84-of-62,100 figures that are widely attributed to it across other blogs.
Source
Otterly.ai, Llms.txt Experiment: What Marketers Get Wrong about llms.txt
Published
2026-02-05
Sample
reported as a single experiment site, server logs, about 90 days
Reproduction
We tried to reproduce this and could not.checked 2026-07-10
This is a claim we would like to be true, because it is convenient for our position on llms.txt. That is precisely why it gets UNREPRODUCED rather than a pass. The qualitative direction is corroborated independently by John Mueller's public comments; the specific numbers are not currently reproducible by us and we will not repeat them. Otterly sells AI search monitoring, so the finding is vendor-interested in the direction of 'a static file is not enough, buy monitoring'. That does not make it wrong.
“Interest in generative engine optimisation is growing rapidly.”
Interest in the TERM peaked in August 2025. Underlying AI usage is a different question, and is still growing.
What the source actually says
Both terms were noise in 2023, measurable in 2024, scaled through 2025, then peaked in late summer 2025 and plateaued. GEO carries roughly twice AEO's search volume, yet the report observes practitioners converging on 'AEO' as the standard label.
“AEO sits ~17% below its September high; GEO ~45% below its August high”
Google Keyword Planner export, 3,751 keywords x 48 monthly data points, June 2022 to May 2026
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the report and confirmed the wording and methodology. Graded DIRECTIONAL rather than VERIFIED because it is single-sourced: we found no second independent dataset measuring term-level trend, and the report gives no absolute volumes. Do not treat the exact percentages as settled.
“Standalone GEO tracking is a durable product category in its own right.”
Contested by someone who tried it. A GEO tracking startup shut down and its founder concluded the opposite.
What the source actually says
Founder Benjamin Houy shut Lorelight down after roughly seven months. His stated reasons: 'Customers were churning because the product didn't change what they needed to do', and 'There's no secret GEO strategy. AI models reward the same fundamentals that already drive SEO and PR.' Consolidation supports the reading: Sitecore acquired Scrunch AI in June 2026, and Adobe agreed to acquire Semrush for about $1.9 billion.
“GEO makes more sense as a feature within existing SEO platforms, not as a standalone category.”
We reproduced this from the primary source.checked 2026-07-10
We fetched the Search Engine Land report and confirmed the quotes, the founder's name and the timeline. Graded DIRECTIONAL, not VERIFIED, because it is one founder's experience with one product, which is evidence but not proof. It is nonetheless the single most useful data point we found, because it is a first-hand account against the speaker's own commercial interest.
“Most AI Overview citations now come from pages that do not rank in Google's organic top 10.”
True as of January 2026, and it was not true six months earlier.
What the source actually says
Ahrefs reports that 37.10% of AI Overview citations come from pages in the organic top 10. The complement, 62.90%, therefore come from outside it. The study attributes the shift to AI Overviews drawing on the SERPs of fan-out sub-queries rather than the original query's SERP. The practical consequence is that optimising only the pages that already rank for your target query addresses a shrinking minority of citations.
“Google is selecting far fewer pages straight from the original SERP (~76% in July 2025 vs. ~38% today).”
We reproduced this from the primary source.checked 2026-07-10
We fetched the article and confirmed the 37.10% organic-only figure, the sample, the authors and the date. Note that the 'most come from outside the top 10' phrasing is our arithmetic complement of Ahrefs' number, not a sentence Ahrefs prints. We flag it because deriving a claim from a source is exactly the step where numbers usually go wrong. Ahrefs sells Brand Radar, so the finding is vendor-interested.
“Most pages an AI cites as a source never get their brand named in the answer.”
True in the study that coined the term: 61.7% were cited without the brand appearing. Small sample, though.
What the source actually says
In 61.7% of cases the AI used a page as a linked source but did not mention the brand in the text of the answer, which undercuts the idea that a citation reliably delivers a brand mention. Note the modest sample: 115 prompts. Perplexity was not included.
“Almost 62% (61.7%) were ghost citations. AI platforms used the page as a source link, but the brand name never appeared in the actual answer.”
3,981 domain appearances across 115 prompts, 14 countries, on ChatGPT, Gemini, Google AI Overviews and Google AI Mode
Reproduction
We reproduced this from the primary source.checked 2026-07-10
We fetched the article and confirmed the 61.7% figure, the 3,981 domain appearances, the 115 prompts and the date. We grade it VERIFIED because the number reproduces exactly, while flagging that 115 prompts is a thin base for how broadly this stat is now generalised. Semrush sells an AI visibility toolkit.
“Brand mentions correlate with AI visibility about three times more strongly than backlinks.”
The 0.664 vs 0.218 numbers reproduce exactly. The word the claim drops is 'weak'.
What the source actually says
Branded web mentions correlate with Google AI Overview visibility at Spearman 0.664, against 0.218 for backlinks, which is roughly the three-to-one the claim states. But the authors add the part usually dropped: 'correlation does not equal causation', and 'all the factors we studied revealed moderate to very weak correlations'. So mentions beat backlinks relatively, while both are weak in absolute terms, and the scope is AI Overviews, not AI search generally.
“Web mentions (0.664) correlate much more strongly than backlinks (0.218).”
We reproduced this from the primary source.checked 2026-07-10
We fetched the article and confirmed both correlation figures, the 75,000-brand sample, the method, the date and the caveats. The bare claim reproduces, so it is VERIFIED. What is misleading is the common extension of it, that mentions therefore 'matter more than links', which the study neither tests nor supports.
Found something we got wrong?
Send the primary source. If it holds up, we regrade the claim in public and log the change in
corrections, with the date and what changed. We do not
silently edit pages.