{"id":100113,"date":"2026-07-09T09:38:10","date_gmt":"2026-07-09T09:38:10","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/100113\/"},"modified":"2026-07-09T09:38:10","modified_gmt":"2026-07-09T09:38:10","slug":"google-leads-ai-discovery-as-chatgpt-dominates-llm-referrals","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/100113\/","title":{"rendered":"Google leads AI discovery as ChatGPT dominates LLM referrals"},"content":{"rendered":"

Previsible said Google remains the main surface for AI-influenced brand discovery, even as ChatGPT dominates measurable referrals from standalone AI assistants.<\/p>\n

The AI discovery agency released the third edition of its AI Traffic Study, which tracks generative engine optimisation and modern search trends. The report covers data from November 2024 to May 2026 and analyses 6.77 million LLM-driven sessions across 166 websites.<\/p>\n

Previsible said the study is based on 166 Google Analytics 4 properties and measures referral traffic from standalone LLM platforms. The company excluded Google AI Overviews from the standalone LLM dataset, saying Google\u2019s AI search features operate under a different measurement model and do not produce trackable referral sessions in the same way.<\/p>\n

Google leads AI discovery<\/p>\n

The study found that AI discovery inside Google, including AI Overviews and AI Mode, represents a larger volume of AI-influenced traffic than standalone LLM platforms combined.<\/p>\n

The websites included in the study span SaaS, e-commerce, finance, legal, health, insurance, education, publishing, and ticketing. The report identified Google\u2019s AI Overviews and AI Mode as the main surfaces marketers should focus on in the second half of 2026.<\/p>\n

The study separately measured referral traffic from standalone AI assistants. ChatGPT accounted for most measurable LLM referral traffic in that channel.<\/p>\n

The report also found that total monthly standalone LLM-referred sessions grew 9.9 times between November 2024 and May 2026. Monthly sessions fell in November 2025 before recovering in December.<\/p>\n

Monthly LLM-driven sessions reached 644,478 in May 2026, up from 65,249 in November 2024.<\/p>\n

Monthly standalone LLM-referred sessions fell 50% in November 2025, with the decline driven mainly by ChatGPT referrals. ChatGPT referrals dropped from 448,412 in October 2025 to 213,345 in November 2025, before recovering to 442,609 in December 2025.<\/p>\n

The report did not attribute the November decline to a single confirmed cause.<\/p>\n

ChatGPT dominates standalone referrals<\/p>\n

Among standalone assistants, ChatGPT remained the largest source of trackable referral traffic. The study found that ChatGPT accounted for 92.4% of standalone AI referral traffic across the websites analysed.<\/p>\n

ChatGPT\u2019s share increased from about 84% in Previsible\u2019s December 2025 review to 92.4% in the latest study. At the time, Perplexity held 8.9%, Gemini 4.5%, Copilot 2.1%, and Claude 0.6%.<\/p>\n

ChatGPT\u2019s standalone referral traffic rose from 47,606 sessions in November 2024 to 610,910 in May 2026. That represented a 12.8 times increase over the 19-month period.<\/p>\n

Other AI assistants also recorded referral traffic growth during the study period. Gemini grew 3.2 times and became the second most visible model behind ChatGPT. Claude grew 64 times over the tracked period and moved ahead of Perplexity in March 2026.<\/p>\n

Gemini\u2019s trackable referral traffic rose from 5,598 sessions in November 2024 to 18,119 in May 2026.<\/p>\n

Claude\u2019s referral traffic rose from 133 sessions in November 2024 to 8,528 in May 2026. The report said Claude overtook Perplexity in monthly referral sessions in March 2026 and remained ahead through May.<\/p>\n

Claude referrals were more common among developers, technical buyers, and professional services audiences, according to the study. The report also found differences in AI referral patterns across industries.<\/p>\n

The study also pointed to declines from some standalone AI referral sources. Perplexity peaked at 17,507 monthly sessions in March 2025 before falling to 6,788 in May 2026. Copilot dropped from 8,651 sessions in August 2025 to 339 in May 2026.<\/p>\n

AI traffic varies by industry<\/p>\n

AI referral traffic to e-commerce content rose 37 times, according to the study. Product pages became the main landing surface for e-commerce LLM traffic.<\/p>\n

Insurance also recorded growth in AI traffic penetration, rising 18.9 times to 1.51% of total sessions. Education grew 5.4 times, while finance increased from 0.56% to 1.19%. SMB websites rose from 0.4% to 1.71%.<\/p>\n

Health was the only vertical in the dataset where AI traffic penetration declined, falling from 0.23% to 0.17%. The report showed that LLM traffic remained a small share of total sessions across the dataset, but concentration varied by industry and page type.<\/p>\n

The report found that AI-referred traffic does not land on the same types of pages across industries. In SaaS, internal search pages accounted for 34.6% of LLM referrals, while news pages accounted for 54% of publisher referrals. In education, course pages accounted for 52% of LLM referrals.<\/p>\n

In publishing, news pages accounted for 54% of LLM referrals in the category. The study found that LLM penetration remained low at 0.08% against more than 120 million organic sessions.<\/p>\n

In e-commerce, product pages were the main landing surface for LLM traffic. The study found that e-commerce AI traffic was almost entirely driven by ChatGPT.<\/p>\n

In health, about pages accounted for 42.1% of LLM referrals, which the report linked to users checking the credibility of a source after being directed by an AI assistant. In legal, referrals were more evenly distributed across blog, about, contact, and location pages.<\/p>\n

In financial services, blog content received the largest share of LLM referrals, while some location and conversion pages also recorded LLM traffic. Some conversion pages, including enrolment, sign-up, and product-entry pages, recorded LLM-to-total traffic ratios above 2%.<\/p>\n

Across industries, AI-referred traffic landed on internal search results pages roughly 25% of the time, according to the study.<\/p>\n

Search foundations remain central<\/p>\n

David Bell, Previsible\u2019s chief product officer and author of the report, said website structure and content signals remain important as AI becomes part of discovery.<\/p>\n

\u201cThe foundation brands built in search matters more than ever,\u201d Bell said. \u201cStart by becoming a source Google\u2019s AI results want to cite by building the site architecture, and content signals AI systems rely on to cite you, then win ChatGPT as the leading standalone surface.\u201d<\/p>\n

Bell said teams that focus on AI search now will be better positioned to appear in AI-generated results. Previsible recommended five areas of focus: building citation-worthy evidence, improving authority across trusted third-party sources, making websites easier for AI systems to read and extract, optimising for answer journeys, and measuring business impact instead of broad visibility alone.<\/p>\n

The report also said marketers should measure AI traffic by page type rather than relying only on site-wide averages. The study found that AI traffic varied by page type, including pricing, product, course, and conversion pages.<\/p>\n

Previsible CEO Jordan Koene said the study draws attention to users who reach and interact with brand websites through AI-driven discovery.<\/p>\n

\u201cDavid\u2019s research brings focus to one of the most important, and often overlooked, parts of AI search: the value of engaged users who visit and interact with brand websites,\u201d Koene said.<\/p>\n

Koene said the findings can affect how brands measure AI-driven discovery, build optimisation strategies, and improve web experiences and messaging for customers.<\/p>\n

(Photo by Shutter Speed<\/a>)<\/p>\n

See also: AI try-on linked to higher ecommerce conversion<\/a><\/p>\n

\"\"\/<\/a><\/p>\n

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