LLM SEO: The 2026 Guide to Getting Cited by ChatGPT, Gemini and Claude

Search behaviour is splitting between the classic results page and conversational answers, and LLM SEO is the name most marketers use for the second half of the job. You will also see it called GEO (generative engine optimization), AEO or LLMO. The labels differ, the mechanics are the same, and they are concrete enough to work on methodically.

What is LLM SEO?

LLM SEO is the set of actions that increase the probability that a language model mentions, recommends or cites your brand when it answers a question. Classic SEO aims for a position in a list of ten links. LLM SEO aims for a place inside a synthesized answer, where often only three to five brands or sources are named.

The goal has two forms, and they are worth separating:

• Mention: the model names your brand in its answer (for example, in a list of recommended tools).
• Citation: the model links to one of your pages as a source for what it says.

A brand can be mentioned without being cited (the model knows it from training) and cited without being recommended (your page is used as a neutral source). Good LLM SEO works on both.

How do LLMs choose their sources?

Through two channels: parametric memory built during training, and live retrieval from the web when the model searches. Understanding which one is at work for a given question tells you what lever to pull.

Retrieval is the mechanism called retrieval-augmented generation (RAG). When a model searches, it often splits the question into several sub-queries (query fan-out), retrieves results for each, and keeps the passages that answer best. Ranking well in classic search for those sub-queries therefore remains one of the strongest predictors of being cited. Google states that its AI features, such as AI Overviews, rely on the same index and the same quality systems as Search, and that no special markup is required to appear in them (Google Search Central).

What makes a passage citable?

A passage gets cited when it answers one question completely, on its own, with a verifiable fact. The model extracts a chunk of a few sentences, so that chunk must make sense without the rest of the page.

The research supports this. The Princeton study that coined the term GEO tested several rewriting methods and found that adding sources, quotations and statistics increased visibility in generated answers by up to about 40% on their benchmark (Aggarwal et al., GEO). Keyword stuffing, by contrast, did not help.

The practical rules:

• Answer first. Put the direct answer in the first sentence under each heading, then develop.
• One section, one question. Phrase headings as the questions people type, and never write "as seen above".
• Name things precisely. Repeat the subject instead of "it" or "this tool", so the extracted passage keeps its meaning.
• Add numbers with their source. A figure attributed to a named study is more quotable than an opinion.
• Use tables and lists for anything comparable; they are the easiest format to extract.
• Bring information gain. Original data, first-hand tests or an expert view give the model a reason to pick your page over ten similar ones.

You can check how a page reads to a model with our free LLM readability checker.

Why does entity consistency matter for LLM SEO?

Because a model trusts what many independent sources say the same way. If your site, your LinkedIn page, review platforms, directories and press articles describe your company with the same name, category and key facts, the model forms a stable association between your brand and that category.

Inconsistent descriptions (an old name on one site, a different category on another, outdated pricing elsewhere) blur that association and increase the risk of errors in the answers. The work is unglamorous and effective:

• Write one reference description of your brand (what it is, for whom, what makes it different) and reuse it everywhere.
• Add Organization structured data with links to your official profiles.
• Be present where the AIs look for opinions: comparison articles, review sites, Reddit or industry forums, depending on your market.
• Earn mentions in third-party content, which feed both training data and live retrieval.

This is the core of entity SEO, and it is often the missing piece for brands whose site is well optimized but who never appear in recommendation lists.

How do you give AI crawlers access to your site?

By allowing the crawlers that fetch pages for live answers, keeping your pages renderable without JavaScript, and staying indexed in the search engines the models use. A page the model cannot fetch will never be cited, however good it is.

Check your robots.txt, your firewall or CDN bot settings (some block AI crawlers by default), and server-side rendering of the main content. Our guide to robots.txt rules for AI crawlers details the directives line by line.

How do you measure LLM SEO results?

By tracking a fixed list of prompts over time and recording mentions, citations and the competitors named instead of you. There is no equivalent of a ranking position, and answers vary from one run to the next, so you measure trends over a panel of questions rather than a single result.

• Build a prompt panel: 20 to 50 real buyer questions, mixing generic ("best tool for X"), comparative ("X vs Y") and problem-based questions.
• Track several models: ChatGPT, Gemini, Claude and Perplexity do not cite the same sources.
• Record four metrics: mention rate, position in the answer, citation of your URLs, and share of voice against competitors.
• Follow AI referral traffic in your analytics (sessions from chatgpt.com, perplexity.ai, gemini.google.com).

Running this by hand quickly becomes tedious, which is why tools such as AI mention tracking repeat the panel every week and list the sources cited for each prompt.

Conclusion

LLM SEO comes down to three things: be accessible to the crawlers, write passages that answer one question completely with sourced facts, and make sure the rest of the web describes your brand the same way you do. Then measure on a stable panel of prompts, because what you do not track you cannot improve.

Sorank runs this in autopilot: it writes and publishes answer-first articles every day, tracks each week whether ChatGPT, Gemini, Claude or Perplexity cite your brand, and shows who is cited in your place. You can start with the 3-day free trial.