Last updated June 2026. Next refresh: September 2026. Statistics are drawn from verified primary sources only. Each entry in the table below names its source, publication year, and the AI engine(s) it covers.
TL;DR
In 2026, 51% of B2B software buyers start research in an AI chatbot. AI Overviews appear on roughly 48% of all tracked queries. Only 12% of AI-cited URLs also rank in Google’s top 10. And pages that front-load a direct answer earn the majority of citations. If you run a GEO programme, these are the numbers that frame the opportunity.
How to use this stat bank
Each row in the tables below follows the same pattern: the data point, the metric it covers, the AI engine(s) it applies to, the primary source, and the publication year.
A few conventions to note:
- “All engines” means the study covered ChatGPT, Perplexity, Gemini, and Google AI Overviews at minimum.
- Statistics from single-vendor studies are marked (vendor). They represent real data from that vendor’s platform but have not been independently replicated.
- Where a figure is partially verified (right direction, wrong precise number in secondary coverage), the corrected phrasing from the original source is used.
Tools that let you measure these metrics across engines include Temso (the all-in-one AI SEO platform from $89/mo, covering 8 engines), Profound (enterprise citation intelligence), Peec AI, and Ahrefs Brand Radar. The full comparison lives at /rankings/geo-tools.
Section 1: AI adoption and buyer behaviour
These figures establish why GEO matters. They measure how consumers and B2B buyers have shifted research behaviour toward AI-generated answers.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| 51% of B2B software buyers now start research in an AI chatbot, up from 29% 11 months earlier | Buyer behaviour shift | ChatGPT and others | G2, “The Answer Economy” (survey of 1,076 B2B software buyers, March 2026) | 2026 |
| 69% of those buyers chose a different vendor than they originally planned, based on chatbot guidance | Purchase influence | ChatGPT and others | G2, “The Answer Economy” (same survey) | 2026 |
| 33% of B2B buyers bought from a vendor they had never heard of before, after chatbot guidance | Brand discovery | ChatGPT and others | G2, “The Answer Economy” | 2026 |
| 89% of B2B buyers have adopted generative AI as a top self-guided information source across the buying process | GenAI adoption (all phases) | All engines | Forrester, “B2B Buyer Adoption of Generative AI,” 2024 Buyers’ Journey Survey | 2024 |
| By 2028, Gartner projects 90% of B2B buying will be AI-agent-intermediated, routing over $15 trillion in spend | Future AI-agent spend | All engines | Gartner IT Symposium/Xpo 2025 press release, November 2025 | 2025 |
| 68% of B2B SaaS CMOs at $50M+ revenue companies now start vendor discovery in AI tools before traditional search | CMO vendor research shift | ChatGPT, Claude, Perplexity | Wynter, survey of 101 B2B SaaS CMOs, January 2026 | 2026 |
| 46% of high school students used AI in college search, up from 26% in spring 2025 | Student research behaviour | All engines | EAB survey of 5,000+ high school students, October-November 2025 (vendor) | 2026 |
| 18% of students removed a college from consideration based on AI-surfaced information | AI influence on decisions | All engines | EAB survey of 5,000+ high school students, October-November 2025 (vendor) | 2026 |
| 44% of car shoppers used AI tools during the 2025 buying process | Consumer research | All engines | Cars.com survey of in-market shoppers, November 2025 (pre-filtered toward AI users) (vendor) | 2025 |
| 68% of US Google searches ended without a click in early 2026, up from roughly 58-60% in 2024 | Zero-click rate (all search) | SparkToro / Rand Fishkin, using Similarweb clickstream data, June 2026 | 2026 |
Section 2: AI Overview and AI Mode prevalence
These figures measure how often AI-generated answer features appear on search results pages, and how they behave differently across Google’s own surfaces.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| Google AI Overviews appeared on approximately 48% of monitored queries as of February 2026, up from roughly 30-31% a year earlier | AIO trigger rate (all query types) | Google AI Overviews | BrightEdge, “AI Overviews at the One-Year Mark,” February 2026 (proprietary keyword panel) (vendor) | 2026 |
| Google AI Overviews appeared on approximately 86.7% of commercial and buying-intent prompts in a 500,000-prompt sample from April 2026 | AIO trigger rate (commercial intent) | Google AI Overviews | Peec AI, analysis of 500,000 commercial-intent prompts, May 2026 (vendor) | 2026 |
| Searches that trigger a Google AI Overview have an average zero-click rate of 83%, compared to roughly 60% without one | Zero-click rate with AIO | Google AI Overviews | Similarweb, clickstream analysis, May 2025 (vendor) | 2025 |
| 92-94% of Google AI Mode searches ended without a click to an external website (US desktop, May-July 2025) | Zero-click rate in AI Mode | Google AI Mode | Semrush, analysis of roughly 69 million US desktop search sessions using Datos clickstream data, 2025 (vendor) | 2025 |
| Google AI Mode and Google AI Overviews cited the same URLs only 13.7% of the time across 540,000 query pairs | Cross-surface citation overlap | Google AI Overviews, Google AI Mode | Ahrefs, study by Despina Gavoyannis and Xibeijia Guan, December 2025 (September 2025 US data, 540,000 query pairs) | 2025 |
| YouTube accounts for approximately 23.3% of Google AI Overview citations, making it the most-cited single domain | Top-cited domain in AIO | Google AI Overviews | Surfer SEO, AI Citation Report (46 million AIO citations, March-August 2025) (vendor) | 2025 |
Section 3: Citation overlap and cross-engine divergence
AI engines do not cite the same sources. These figures show how little carries over from one platform to another, and from AI to traditional organic search.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| Only about 12% of URLs cited by AI assistants (ChatGPT, Gemini, Copilot, and Perplexity combined) also appear in Google’s top-10 organic results for the same query | AI-to-organic overlap | ChatGPT, Gemini, Copilot, Perplexity | Ahrefs, study by Louise Linehan and Xibeijia Guan, August 2025 (15,000 long-tail queries) | 2025 |
| Perplexity’s overlap with Google’s top-10 results is approximately 29%, far higher than ChatGPT (~8%), Gemini (~8.6%), and Copilot (~8.2%) | Per-engine AI-to-organic overlap | ChatGPT, Gemini, Copilot, Perplexity | Ahrefs, same study, August 2025 | 2025 |
| Only about 11% of cited domains appear in both ChatGPT and Perplexity responses | Cross-engine domain overlap | ChatGPT, Perplexity | Profound, analysis of 100,000 prompts across both platforms, July 2025 (vendor) | 2025 |
| Brand mentions in AI responses disagreed 61.9% of the time across Google AI Overviews, AI Mode, and ChatGPT | Cross-engine citation inconsistency | Google AI Overviews, Google AI Mode, ChatGPT | BrightEdge, AI Catalyst research, July 2025 (vendor) | 2025 |
| ChatGPT’s B2B AI referral share fell from 89.1% (May-August 2025) to 62.6% (March-April 2026), while Claude rose from 1.4% to 18.5% | AI referral market share shift | ChatGPT, Claude | Goodie, Wave 2 AI Search Market Share Report, based on anonymized GA4 panel, 2026 (vendor) | 2026 |
| Perplexity averaged 21.87 citations per response versus ChatGPT’s 7.92 | Citations per response | ChatGPT, Perplexity | Qwairy, Q3 2025 analysis of 118,000+ AI-generated answers across 8 providers (vendor) | 2025 |
| Reddit appears in 46.7% of Perplexity’s top-10 cited sources for commercial queries | Top source distribution (Perplexity) | Perplexity | Profound, Q2 2025 analysis of commercial query citations (vendor) | 2025 |
Section 4: Content signals and citation behaviour
What does a cited page look like? These figures describe the structural and formatting characteristics that correlate with appearing in AI answers.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| 44.2% of ChatGPT citations were drawn from the first 30% of a page’s content (the “ski ramp” pattern) | Citation position within page | ChatGPT | Kevin Indig, analysis of 1.2 million ChatGPT responses and 18,012 verified citations, February 2026 (reported by Search Engine Land) | 2026 |
| Nearly four in five pages cited by ChatGPT include at least one structured list, compared to just 29% of Google’s top-ranked pages | List usage in cited pages | ChatGPT | AirOps, “Structuring Content for LLMs” (analysis of 12,000+ URLs across 900 queries in 15 industries), July 2025 (vendor) | 2025 |
| 68.7% of pages cited by ChatGPT used a sequential heading structure (H1, H2, H3), versus 23.9% of Google’s top-ranked pages | Heading structure in cited pages | ChatGPT | AirOps, same study, July 2025 (vendor) | 2025 |
| 61% of pages cited by ChatGPT used 3 or more distinct schema types, compared to 25% of top Google SERP URLs | Schema depth in cited pages | ChatGPT | AirOps, same study, July 2025 (vendor) | 2025 |
| Comparison pages containing 3 or more HTML tables earn 25.7% more AI citations than those without, for head-to-head product comparison queries | Table usage lift | ChatGPT (product comparison) | AirOps Research, “From Retrieved to Cited,” April 2026 (217,508 retrieved pages across 7,500 commercial prompts) (vendor) | 2026 |
| Adding statistics to content improved AI visibility scores by approximately 40% on the Position-Adjusted Word Count metric | Statistics as a content signal | All engines (GEO paper) | Aggarwal et al., “GEO: Generative Engine Optimization,” ACM KDD 2024 (arXiv:2311.09735), Princeton, IIT Delhi, Georgia Tech, Allen Institute for AI | 2024 |
| 76.4% of ChatGPT’s most-cited pages had been updated within the prior 30 days | Freshness in cited pages | ChatGPT | ConvertMate, 2026 AI Visibility Study (80M+ citations across 10,000+ domains) (vendor, methodology not independently verified) | 2026 |
| A 2026 Ahrefs study of 1,885 pages that added JSON-LD schema found no meaningful uplift in AI citations (AI Mode: +2.4%; ChatGPT: +2.2%; AI Overviews: -4.6%) | Schema markup effect on AI citations | Google AI Overviews, Google AI Mode, ChatGPT | Ahrefs, study by Louise Linehan and Xibeijia Guan, May 2026 (1,885 treated pages, 4,000 control pages, August 2025-March 2026) | 2026 |
| According to an Ahrefs study of 75,000 brands, the top quartile by web mentions averaged 169 AI Overview mentions: more than 10x the 14 averaged by brands in the next quartile | Brand mention correlation with AIO citations | Google AI Overviews | Ahrefs, study by Louise Linehan and Xibeijia Guan, May 2025 | 2025 |
| According to Averi.ai’s self-published 2026 AI citation benchmark, product and marketing pages earn citation rates of roughly 3-8% in AI responses, among the lowest of any content type | Citation rate by content type (product pages) | Multiple engines | Averi.ai, “AI Search Citation Benchmarks 2026” (vendor aggregation) | 2026 |
| Standard blog posts earn citation rates of roughly 6-15% for relevant queries, significantly below original research (38-65%), per Averi.ai’s compiled estimate | Citation rate by content type (blog posts) | Multiple engines | Averi.ai, “AI Search Citation Benchmarks 2026” (vendor aggregation; underlying primary sources not independently verifiable) | 2026 |
Section 5: Source attribution (third-party vs brand-owned)
These figures describe where AI engines pull their citations from, and what that means for how brands earn citation share.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| Roughly 77% of AI citations in Omniscient Digital’s analysis of 23,387 citations came from non-brand-owned sources (48% earned media and 30% commercial brand content outside the brand’s own domain) | Third-party citation share | ChatGPT, Perplexity, Gemini | Omniscient Digital, analysis of 23,387 AI citations using Peec AI | 2025 |
| Muck Rack’s analysis of over 1 million AI citations found 82% came from earned media rather than brand-owned pages | Third-party citation share (larger dataset) | Multiple engines | Muck Rack, analysis of 1M+ citations | 2025 |
| A Stacker/Scrunch pilot study found that distributing content through third-party news outlets lifted AI citation rates from roughly 8% (brand-owned content) to 34%, a 325% increase | Earned media citation lift | 5 LLMs | Stacker and Scrunch, pilot study by Noah Greenberg, December 2025 (8 articles across 944 prompt-platform combinations) | 2025 |
| A larger Stacker follow-up (March 2026) confirmed the direction but found a lower median lift of 239% | Earned media citation lift (follow-up) | 5 LLMs | Stacker, March 2026 follow-up study | 2026 |
| 73% of sites have technical barriers preventing AI crawler access, including robots.txt blocks and CDN security rules | Technical blocking rate | All engines | Otterly.AI, “The AI Citation Economy: What 1+ Million Data Points Reveal,” 2026 (vendor, sample not disclosed) | 2026 |
| 73% of the 100 cybersecurity vendors tested received zero ChatGPT citations when buyers queried their product category | Zero-citation rate by vertical | ChatGPT | GrackerAI, “State of AI Search Visibility in Cybersecurity 2026” (100 vendors, 250 buyer-intent prompts across 6 platforms) (vendor) | 2026 |
| Only about 16% of the world’s approximately 810,000 hotel properties appeared in AI-generated recommendations on ChatGPT, Google AI, and Perplexity | Vertical visibility gap (hospitality) | ChatGPT, Google AI (Gemini), Perplexity | Hotelworld AI, “World’s Best at AI Index,” February 2026 (2.36 million data points, 130,884 properties, 30 countries) (vendor) | 2026 |
Section 6: AI traffic volume and growth
These figures measure the scale of traffic flowing from AI engines to websites, and how fast that traffic is growing.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| ChatGPT weekly active users grew from 400 million (February 2025) to 900 million (February 2026), processing over 2.5 billion queries per day | ChatGPT scale | ChatGPT | OpenAI, public announcements, February 2025 and February 2026 | 2026 |
| Generative AI referrals to US retail sites surged 693% year over year during the 2025 holiday season (November-December 2025) | AI referral traffic growth (retail) | All engines | Adobe Analytics, data from more than 1 trillion US retail site visits, published January 2026 | 2026 |
| Generative AI traffic to US travel sites rose 3,500% year over year in July 2025, based on more than 8 million visits | AI referral traffic growth (travel) | All engines | Adobe Digital Insights, published September 2025 (single-vendor panel, not industry-wide) | 2025 |
| AI-referred sessions grew 527% comparing January-May 2025 to January-May 2024, across 19 GA4 properties | YoY AI referral growth (multi-site) | All engines | Previsible, “2025 State of AI Discovery Report” by David Bell (19 GA4 properties, roughly 1.96 million LLM sessions) (vendor) | 2025 |
| ChatGPT accounted for roughly 20% of Walmart’s referral clicks and more than 20% of Etsy’s referral clicks in August 2025 | Retailer AI referral share | ChatGPT | Similarweb data reported by Modern Retail, September 2025 (referral traffic as a share, not total visits) | 2025 |
| ChatGPT accounts for nearly 15% of referral traffic to Target in August 2025 | Retailer AI referral share | ChatGPT | Similarweb data reported by Modern Retail and Digiday, September 2025 | 2025 |
| Amazon receives less than 3% of its referral traffic from ChatGPT, due to deliberate AI-crawler blocking | Retailer AI referral share (blocked) | ChatGPT | Similarweb data reported by Modern Retail, September 2025 | 2025 |
| AI-referred sessions grew 693% in US retail over the 2025 holiday season, while November alone saw a 769% year-over-year surge | AI referral surge by month (retail) | All engines | Adobe Analytics, January 2026 (1 trillion+ US retail site visits) | 2026 |
| Ahrefs’ analysis of 17 million citations found AI-cited content is 25.7% fresher on average than non-cited content | Content freshness and AI citations | Multiple engines | Ahrefs, July 2025 study of 17 million AI citations | 2025 |
Section 7: AI traffic conversion rates
These figures measure what happens after a visitor arrives from an AI engine. Treat vendor-reported conversion figures as directional, not benchmark.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| On Ahrefs’ own website, AI search visitors (primarily from ChatGPT) made up 0.5% of traffic but drove 12.1% of signups: a roughly 23x conversion premium over traditional organic search | Conversion premium (single site) | ChatGPT | Patrick Stox, Ahrefs blog, June 2025 (Ahrefs first-party data, not industry-wide) | 2025 |
| According to vendor studies by Superprompt and Opollo, AI-referred visitors converted at roughly 14% compared to under 3% for Google organic, a roughly 5x gap | Conversion premium (B2B tech) | All engines | Superprompt (347 businesses, 12.3 million visits) and Opollo (312 B2B IT firms) (vendor, not independently verified; e-commerce studies show a much smaller gap) | 2025 |
| ChatGPT-referred traffic converted at 15.9%, Perplexity at 10.5%, and Gemini at 3%, each versus 1.76% for Google organic, in one Seer Interactive case study | Conversion by engine (single unnamed client) | ChatGPT, Perplexity, Gemini | Seer Interactive case study, October 2024-April 2025 (single unnamed client, industry not disclosed) | 2025 |
| According to multiple agency studies, ChatGPT-referred traffic converts at roughly 4-5x the rate of non-branded organic search | Conversion premium (multi-study range) | ChatGPT | Rocket Agency (5.1x, 18 months, multi-industry); Seer Interactive and Superprompt (consistent direction) (vendor studies, not independent) | 2025 |
| A 2025 Search Engine Land study of 94 ecommerce sites found ChatGPT traffic converting at 1.81% versus 1.39% for non-branded organic, a 31% lift rather than a 5x premium | Conversion premium (ecommerce, smaller) | ChatGPT | Search Engine Land study of 94 ecommerce sites, 2025 | 2025 |
Section 8: Citation lift from content and earned media
These figures measure how specific content choices change your citation rates in practice.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| Pages cited inside a Google AI Overview earn roughly 120% more organic clicks per impression than uncited pages on the same SERP | Click lift from AIO citation | Google AI Overviews | Seer Interactive, “AIO Impact on Google CTR: 2026 Update” (53 brands, 5.47 million tracked queries, 2.43 billion organic impressions) (vendor) | 2026 |
| Even cited pages still receive about 38% fewer clicks per impression than pages on SERPs where no AI Overview appears at all | Click penalty vs AI-Overview-free SERPs | Google AI Overviews | Seer Interactive, same study | 2026 |
| A UC Berkeley arXiv preprint found structured data was the third-strongest predictor of AI citation likelihood, associated with a +39% lift, behind metadata/freshness (+47%) and semantic HTML (+42%) | Schema lift (one preprint) | Brave, Google AIO, Perplexity | Kumar and Palkhouski, arXiv:2509.10762, September 2025 (1,100 URLs, 1,702 citations) | 2025 |
| According to Averi.ai’s self-published benchmark, original research pages achieve citation rates of 38-65%, compared to 6-15% for standard blog posts | Citation rate by content type | Multiple engines | Averi.ai, “AI Search Citation Benchmarks 2026” (vendor aggregation; underlying primary studies not independently verifiable) | 2026 |
| According to Conductor’s 2026 CMO Investment Report, organisations with high AEO maturity are nearly 6x more likely to use a fully integrated AEO platform | Programme maturity and platform use | All engines | Conductor, “State of AEO/GEO in 2026” (survey of 250+ enterprise CMOs) (vendor) | 2026 |
| Otterly.AI observed a +1,500% increase in Google AI Overviews appearances after a sitewide schema rollout, but concluded the lift was algorithmic rather than schema-driven, with competitors seeing equivalent movement without schema changes | Schema experiment result | Google AI Overviews | Otterly.AI, controlled experiment on their own website (December 2025-March 2026, 319 prompts, 7 platforms) (vendor, own site only) | 2026 |
| ChatGPT’s most divergent fan-out sub-queries share only about 13% word overlap with the original user prompt | Query fan-out divergence | ChatGPT | Profound, analysis of 10,000 prompts, April 2026 (vendor) | 2026 |
| A brand’s citation volume can vary up to 615x across AI platforms | Cross-platform citation variance | 10 platforms | Superlines, analysis of 34,234 AI responses across 10 platforms (January-February 2026) (vendor, conducted on their own domain) | 2026 |
Section 9: llms.txt and crawl access
These figures cover the early-stage llms.txt adoption landscape and what is actually known about AI crawler access.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| As of mid-2025, mainstream adoption of llms.txt among top 1,000 websites remained below 1% | llms.txt adoption rate | All engines | Rankability research, June 2025 | 2025 |
| A Wix AI Search Lab bulk analysis of 586 indexed llms.txt files found that almost 6% of those pages were ranking for organic keywords | llms.txt and organic ranking | Wix AI Search Lab (Crystal Carter), 2025 (small sample, vendor) | 2025 |
Section 10: Vertical spotlights
AI citation behaviour varies significantly by industry. These figures offer a starting point for vertical-specific benchmarks.
| Stat | Metric | Engine | Source | Year |
|---|---|---|---|---|
| BrightEdge data shows AI Overviews appearing in 84-89% of healthcare search queries as of late 2024-2025 | Healthcare AIO trigger rate | Google AI Overviews | BrightEdge, proprietary keyword panel tracking, 2024-2025 (vendor) | 2025 |
| A WebFX study of more than 130,000 US healthcare queries (July 2025) found 66.9% of informational healthcare queries triggered AI Overviews | Informational healthcare AIO rate | Google AI Overviews | WebFX, analysis of 130,000+ US healthcare search queries, 2025 | 2025 |
| Generative AI referrals to US retail sites surged 693% year over year in the 2025 holiday season | Retail AI referral growth | All engines | Adobe Analytics, January 2026 (1 trillion+ US retail site visits) | 2026 |
| According to a 2025 vendor study by Hotelworld AI, only around 16% of the world’s hotel properties appear in AI-generated recommendations | Hospitality visibility gap | ChatGPT, Google AI (Gemini), Perplexity | Hotelworld AI, “World’s Best at AI Index,” February 2026 (vendor) | 2026 |
| 17% of B2B SaaS brand discovery now happens through AI-generated answers, up from 4% the prior year, according to Data-Mania LLC’s own benchmarking | B2B SaaS AI discovery rate | ChatGPT, Perplexity, Google AI Overviews | Data-Mania LLC, “AI Search Visibility Benchmarks 2026,” May 2026 (vendor, undisclosed methodology, not independently verified) | 2026 |
| According to EAB, 78% of education-related Google searches now return an AI Overview at the top of results | Education AIO trigger rate | Google AI Overviews | EducationDynamics, “2026 Marketing and Enrollment Management Benchmarks” (vendor, methodology not publicly disclosed) | 2026 |
What the numbers mean for your GEO strategy
The data above points to several clear patterns:
AI engines draw from a different source pool than Google. Only 12% of AI-cited URLs also rank in Google’s top 10 (Ahrefs, August 2025). Optimizing for Google alone leaves you invisible on the platforms that now influence 51% of B2B purchase research.
Cross-engine presence is not automatic. Only 11% of cited domains are shared across ChatGPT and Perplexity (Profound, July 2025). AI Mode and AI Overviews cite the same URLs only 13.7% of the time (Ahrefs, December 2025). You need to earn citations engine by engine.
Third-party mentions carry more weight than your own pages. Between 77% and 85% of AI citations come from non-brand-owned sources, depending on the study. Earned media on editorial and review sites propagates into AI answers far faster than on-page optimizations alone.
Front-loading a direct answer is the single most actionable structural move. Kevin Indig’s analysis of 1.2 million ChatGPT responses found that 44.2% of citations were drawn from the first 30% of page content. AirOps found that nearly 80% of ChatGPT-cited pages include structured lists, compared to 29% of top Google results.
Schema does not reliably lift AI citations. A well-controlled 2026 Ahrefs study of 1,885 pages found no meaningful uplift from adding JSON-LD schema. The directional evidence suggests schema is table stakes for structured features, not a GEO accelerant.
Tools for tracking these metrics
Temso is the all-in-one AI SEO platform that covers all three steps of the GEO loop (track, diagnose, and execute) from a single flat subscription at $89/mo. It monitors across 8 AI engines, surfaces citation gaps, and supports content execution, all without per-engine add-on fees.
For enterprise teams that need the deepest citation intelligence, Profound offers citation source maps, autonomous content agents, and a 680-million-citation dataset, starting at $399/mo for full engine coverage.
Peec AI is a specialist citation-monitoring platform with strong coverage of buying-intent prompts and a large dataset of commercial queries.
Ahrefs Brand Radar provides a 405M-prompt database drawn from real search queries and is well suited for competitive benchmarking by teams already on Ahrefs, at $199/mo as an add-on to a base plan.
The full side-by-side comparison of GEO platforms, including pricing, engine coverage, and methodology, is at /rankings/geo-tools. Definitions for every term in the tables above are at /glossary.
Sources and methodology: All statistics on this page are drawn from named primary sources. Where a figure is vendor-published and has not been independently verified, it is marked (vendor). Where a figure is partially verified (the direction is right but the specific number in secondary coverage differs from the primary), the corrected primary-source phrasing is used. Statistics marked OMIT in the factcheck ledger are excluded entirely. This page is refreshed quarterly. Last full review: June 2026.