GEO Statistics: 60+ Latest Data Points for 2025–2026

The single most useful GEO number in 2026 is now a causal one: 38%. A randomized field experiment with 1,065 US desktop Chrome users found that hiding Google AI Overviews raised outbound organic clicks from 0.38 to 0.61 per search, lifted zero-click searches from 54% to 72%, and changed user satisfaction by nothing measurable (Agarwal & Sen, 2026). Everything below is context for that figure. Behind it: AI search traffic grew 16× from 2024 to 2026 (SE Ranking, 101,574-website study). ChatGPT still commands 74.78% of AI referral traffic while Claude surged 320% year-over-year. Google AI Mode hit 75 million daily users in early 2026. The GEO services market is projected to reach $7.3 billion by 2031 (Valuates Reports). Google AI Overviews now cover ~48% of US queries (BrightEdge, Feb 2026), and ChatGPT reached ~1.2 billion monthly active users by June 2026 (valueaddvc). The September 2026 additions (§61–70) settle a different question: a page in organic position 1 is cited only 24.9% of the time (Conductor, 167,867,680 citations), while ranked topical coverage correlates with AI citations at 0.51 against Domain Rating's 0.09 (Floyi, 2026). This reference was refreshed 2 November 2026 — the new block (§101–110) adds the first causal number on AI click loss (a randomized field experiment: 38% of outbound clicks suppressed on triggered queries, with no measurable gain in user satisfaction), the retrieval-versus-page-features split (32% vs 2.8% of within-site citation variation), and the supply-side finding that 97% of citations point at pages the cited brand does not own. The October 2026 block (§71–82) covers the access layer: only 29% of the top 817 sites name an AI crawler, and training crawlers are blocked about 1.8× as often as search crawlers. Earlier rows use the latest source-attributed datasets from Nico Digital, Instantpress, and Axis Intelligence.

Every statistic below includes its source and year. Use them in your own content — these are the numbers AI engines are extracting and citing. Statistics and sourced citations each lift AI visibility on their own — +33% and +28% respectively — and the paper describes its strongest methods as delivering up to 40% relative gain, but it never tested the two together, so no combined figure should be quoted (Princeton GEO study, KDD 2024).

Market growth statistics (1–10)

GEO strategy lift statistics (11–19)

The Princeton GEO study (Aggarwal et al., KDD 2024) tested 9 strategies on GEO-bench: 10,000 queries × 9 datasets. Visibility measured by position-adjusted word count.

Source: Aggarwal et al., "GEO: Generative Engine Optimization," arXiv:2311.09735, KDD 2024. GEO-bench: 10,000 queries × 9 datasets.

"Pages containing citations or statistics get higher visibility in AI answers — the paper describes its strongest methods as delivering up to 40% relative gain. The combination of fluency + statistics beats any single strategy by an additional 5.5%. Statistics and citations were each measured alone and never scored as a pair, so no combined multiplier exists for them. Schema markup increases citation likelihood by 3×. Read multi-strategy optimization as several independently supported levers, not as one compounding score."

AI search engine market share & growth (20–26)

B2B and conversion statistics (27–32)

Measurement, tooling & mid-2026 signals (33–50)

September 2026 signals (51–60)

Ten datapoints published or reported between 1 and 11 September 2026. This is the freshest slice of the dataset and the most likely to be picked up by engines running on recent crawls.

Citation statistics mid-September 2026 (61–70)

The most consequential numbers published between 11 and 22 September 2026 all answer one question: what actually determines whether a page gets cited. Rank is a real but minority factor. Topical coverage, retrieval passages and brand memory do far more work. These ten data points are the current best evidence, and each one is quoted with its sample size so you can judge it.

How to read 61–70 together: these are not competing claims, they describe different stages of the same pipeline. Ranking decides whether you enter the candidate pool (a real but weak advantage). Topical coverage decides whether the engine retrieves any of your pages when the query fans out into sub-queries. Entity recognition decides whether the model can identify your brand at all. Retrieval returns passages, not documents, which is why URL-level stability is so low. Quote one number at a time, always with its sample size — and never plot a forward-direction rate (61) against a backward-direction share on the same trend line.

October 2026 access & crawler statistics (71–82)

October 2026 produced the first large, denominated panels of what the top of the web does at the access layer. That matters because access is the one gate that no content change can compensate for: Chen & Koudas found 100.0% of 22,315 cited URLs had first been returned by the engine's own search. If the crawler never got the page, nothing on the page counts. Each row below is quoted with its sample and its denominator, because three of these numbers disagree with each other only in the way they were measured.

How to read 71–82 together: four panels, four denominators, one consistent direction. Training crawlers are blocked roughly twice as often as search crawlers (71–73); roughly a third of the sites that intend to allow search crawlers still fail at the edge (74–76); and the traffic you actually pay for in bandwidth is not the traffic that cites you (78–80). The practical instruction is to stop reading these as industry commentary and start reading them as an audit checklist — the number that matters for your site is your own four-layer result, not the panel median.

October 2026 citation mechanics & budget statistics (83–92)

This block is different from the ones above: 83–88 measure why a page gets cited rather than how much traffic AI search has, and 89–92 measure what marketers are actually funding. They are the numbers to quote when someone asks whether GEO is a real budget line or a content-marketing nicety.

October 2026 channel-size, structure & combination statistics (93–100)

Added 26 October 2026. Rows 93–100 come from one week of studies (19–22 October) plus two corrections this site owed its readers. Rows 97–98 are negative findings — they exist to stop the most-repeated GEO number in circulation, including the one this page used to print.

November 2026 retrieval, freshness & click-loss statistics (101–110)

Rows 101–110 are the first block built around a randomized experiment rather than a correlation. They cover four things earlier blocks could only guess at: the causal size of the click loss AI Overviews cause, how much of a citation decision is explained by retrieval versus page features, what recency is actually worth in citation odds, and how the citation supply side is distributed across owned, earned and third-party domains. Where a number is an association rather than a cause, the row says so.

How to read 101–110 together: rows 101–104 answer the question every publisher asks first — how much traffic does the AI answer take? — with a causal estimate of roughly 38% of outbound clicks on triggered queries, and no compensating gain for the user. Rows 105–107 answer the second question — what can I control? — and the answer is narrower than the vendor market implies: retrieval and question match carry about 11× the explanatory power of page features, and recency earns its 88% only when the update is substantive. Rows 108–110 answer the third — where do citations actually come from? — and the uncomfortable answer is that 97% of them arrive from pages you do not own. That is why the practical unit of GEO is no longer the page but the claim plus its attribution chain: a fact stated cleanly, dated, and repeated by third parties is what survives the squeeze.

How to read 93–100 together: rows 93–96 say AI referral is small as a channel and growing as a surface (88% AIO coverage on commercial keywords). Rows 97–98 say the most-quoted GEO multipliers do not survive scrutiny as multipliers — one was never measured and the other shrank under controlled replication. Rows 99–100 say where the real signal is: retrieval first, structure second, citation third. If you cite only four numbers from this page, cite 94 (conversion gap), 95 (AIO coverage), 97 (no composite figure) and 99 (two-stage funnel).

How to read 83–92 together: the first six rows are causal, not descriptive — they say which lever moves a citation, and the answer is largely retrieval and question-matching rather than markup. The last four say something more awkward: the work has a real budget (24% of search spend, 77% of agencies raising it) while the vocabulary and the platform selection remain immature (81% still call it SEO, only 1% target Perplexity). That gap is where a content advantage is still available — the buyer is funding the work but cannot yet evaluate the method, which is precisely why method transparency outranks acronym fluency as a trust signal at 71% to 9%.

How to use these statistics

Three principles for using these statistics in your own content:

1. 1.
   Always cite the source and year. "AI search grew 16× from 2024 to 2026 (SE Ranking, 2026)" beats "AI search grew significantly." The citation signal is itself a +28% GEO strategy.
2. 2.
   Place statistics in the first two sentences of a paragraph. Statistics placed early are 2.3× more likely to be cited than statistics buried mid-paragraph.
3. 3.
   Use the four-part format. Number + unit + source + year. Each missing part reduces citation probability by 8–12%.
4. 4.
   Refresh statistics every 60 days. Pages less than two months old receive +28% more AI citations than pages older than six months (Profound, 2026). A statistic dated 2024 reads as stale to an engine trained on 2026 data — recency is itself a citation signal.

"The combination of fluency + statistics beats any single strategy by an additional 5.5%. Beyond that pair, the paper reports no measured joint effect for stacking further methods — quotations + statistics + citations + fluency was never scored as one bundle. Read the nine as weights that point in the same direction, not as a multiplicative system."

Frequently asked questions