--- title: "LLM SEO Explained: How AI Search Retrieves and Cites | Reneka Digital" description: "What LLM SEO is, how ChatGPT, Gemini, Claude, Copilot, and Perplexity retrieve web pages, what each engine documents, and what actually changes versus classic SEO." url: https://renekadigital.com/blog/llm-seo-explained/ publisher: Reneka Digital, Houston, Texas --- Explainer · 5 minute read # LLM SEO: what it is and how to win it. LLM SEO is the work of getting a brand retrieved, read, and named by large language model assistants when a buyer asks them a question. It shares most of its foundations with classic SEO and differs in three specific places. This explainer covers the mechanics, engine by engine, with sources. ## The short version. - **Answer engines are retrieval systems with a writer on top.** A search index supplies candidate pages, a fetcher reads them, and the model composes an answer with links. You optimize for the retrieval and the reading, not for a rank position. - **Each engine has a documented index and crawler.** ChatGPT uses Bing and its own OAI-SearchBot. Gemini grounds on Google Search. Claude runs [Claude-SearchBot](https://support.claude.com/en/articles/8896518-does-anthropic-crawl-data-from-the-web-and-how-can-site-owners-block-the-crawler). Copilot uses Bing. Perplexity runs PerplexityBot. - **Google says no special optimization exists.** Its documentation states that [there are no additional requirements to appear in AI Overviews or AI Mode](https://developers.google.com/search/docs/appearance/ai-features) and that eligibility is the same as for a normal snippet. - **What changes:** passages are judged one at a time, brand mentions on other sites drive visibility more than links, and freshness is rewarded more than in classic results. ## How an answer engine builds an answer. The pattern behind ChatGPT search, Gemini, Claude, Copilot, Perplexity, and Google's AI Overviews is retrieval-augmented generation. The user's question is turned into one or more search queries. A search index returns candidate documents. The engine fetches and reads them, often in chunks. The model writes an answer conditioned on those chunks and attaches citations to the ones it drew from. Three consequences follow. A page must be in the underlying index to be a candidate at all. The fetch has to return readable HTML, because the fetchers do not run scripts. And the unit of selection is a passage, not a page, so a section that answers a question completely in its first sentences is more likely to be quoted than a page that is excellent overall but buries the answer. ## Who indexes what. | Engine | Search index behind it | Crawler or fetcher it documents | Source | |---|---|---|---| | ChatGPT search | Bing plus OpenAI's own index | OAI-SearchBot (search), ChatGPT-User (user fetch), GPTBot (training) | [OpenAI](https://developers.openai.com/api/docs/bots) | | Google AI Overviews and AI Mode | Google Search | Googlebot. Google-Extended controls Gemini app and Vertex AI training and grounding, and does not affect Search inclusion or ranking | [Google](https://developers.google.com/search/docs/appearance/ai-features) | | Gemini (grounded) | Google Search | Googlebot | [Google](https://ai.google.dev/gemini-api/docs/google-search) | | Claude | Anthropic's search index | Claude-SearchBot (search), Claude-User (user fetch), ClaudeBot (training) | [Anthropic](https://support.claude.com/en/articles/8896518-does-anthropic-crawl-data-from-the-web-and-how-can-site-owners-block-the-crawler) | | Microsoft Copilot | Bing | Bingbot | Microsoft | | Perplexity | Perplexity's own index | PerplexityBot (search), Perplexity-User (user fetch) | [Perplexity](https://docs.perplexity.ai/docs/resources/perplexity-crawlers) | The Bing dependency is the one most B2B teams have never acted on. Seer Interactive found [87% of ChatGPT citations matched Bing top results](https://www.seerinteractive.com/insights/87-percent-of-searchgpt-citations-match-bings-top-results) while only 56% matched Google's. A site that has only ever been managed through Google Search Console is invisible to a large share of the retrieval that feeds ChatGPT and Copilot. Anthropic's documentation is a useful example of how to read these bot lists. It names three agents and states that all three honor robots.txt. [Claude-SearchBot](https://support.claude.com/en/articles/8896518-does-anthropic-crawl-data-from-the-web-and-how-can-site-owners-block-the-crawler) "navigates the web to improve search result quality for users"; Claude-User visits pages when a person asks Claude a question; ClaudeBot collects content for training. A site can decline training and still be fully citable, as long as it does not block the search and user agents. ## Google's position, in its own words. > There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary.[Google Search Central, AI features and your website](https://developers.google.com/search/docs/appearance/ai-features) The same page states that to be eligible as a supporting link, a page must be indexed and eligible to be shown in Google Search with a snippet, and that nosnippet, data-nosnippet, max-snippet, and noindex are the controls that limit what AI features can use. Google's May 2025 guidance on [succeeding in AI search](https://developers.google.com/search/blog/2025/05/succeeding-in-ai-search) adds that AI Mode users ask longer questions and that unique, valuable content, good page experience, sound technical foundations, structured data, and multimodal content are the levers. So the foundations of classic SEO carry straight over: crawlable HTML, one canonical URL per page, fast pages, accurate titles, and content that says something a competitor's page does not. ## Three real differences. **Passages, not pages.** The [Aggarwal et al., GEO: Generative Engine Optimization, KDD 2024](https://arxiv.org/abs/2311.09735) paper measured how page edits change a source's share of a generated answer and found gains of up to 40% from adding sourced statistics, attributed quotes, inline citations, and clearer prose. The unit that gets quoted is a self-contained section. **Mentions, not links.** In Ahrefs' [75,000-brand study](https://ahrefs.com/blog/ai-overview-brand-correlation/), brand web mentions correlated with AI Overview visibility at 0.664 and backlinks at 0.218. Digital PR that gets the name into sentences on trusted pages outperforms link building that gets a URL into a footer. **Freshness, measured.** AI-cited pages were [25.7% newer than organic results](https://ahrefs.com/blog/do-ai-assistants-prefer-to-cite-fresh-content) across 16.975 million cited URLs, and ChatGPT's citations were 458 days newer on average. Real refreshes with visible dates are part of the program, not an afterthought. One more difference is what does not work. A 137,000-domain study found that [97% of llms.txt files received zero traffic](https://ahrefs.com/blog/llmstxt-study/) in May 2026 and that Google Search ignores the file. Ahrefs' controlled test found [no major uplift in citations](https://ahrefs.com/blog/schema-ai-citations/) from adding schema. Neither hurts; neither is a lever. ## One framework across engines. Reneka runs every engagement on the AAIA framework (Audit, Architect, Implement, Amplify) with one scorecard across ChatGPT, Perplexity, Gemini, and Claude. The [platform page](https://renekadigital.com/platform/) covers the audit, the citation intelligence reporting, and the GEO Engine. The [AI search glossary](https://renekadigital.com/resources/glossary/) defines the vocabulary, and the [AI search statistics page](https://renekadigital.com/resources/ai-search-statistics/) collects the numbers used in this article with their sources. ## Common questions. ### Is LLM SEO the same as GEO, AEO, and AI SEO? Yes. The four names describe the same practice: getting a brand retrieved and named in answers from large language model assistants. GEO (generative engine optimization) is the term used in the academic literature, and AI SEO is the term buyers search for most. ### Do I need llms.txt or special markup for AI search? No engine has documented using llms.txt, Google says Search ignores it, and Ahrefs found 97% of such files were never requested. Google also states there are no additional requirements for AI Overviews or AI Mode. Standard crawlable HTML with clear, sourced passages is what the engines use. ### Which engine should a B2B brand prioritize? Start with the index that feeds the most surfaces: Bing feeds ChatGPT search and Copilot, and Google Search feeds AI Overviews, AI Mode, and grounded Gemini. Verify the site in both Google Search Console and Bing Webmaster Tools before doing anything engine-specific. --- Source: https://renekadigital.com/blog/llm-seo-explained/ Reneka Digital, Houston, TX 77002. info@renekadigital.com. (346) 224-6908.