LLM SEO: How to Get Cited by Large Language Models
A language model does not hand you a list of links. It writes one answer. LLM SEO is how your page ends up inside that answer.
This guide explains how models like ChatGPT, Claude, Gemini and Perplexity choose the text they quote, and what to change on your pages so they choose yours.
Get Your GEO ScoreWhat Is LLM SEO?
LLM SEO is the practice of writing and structuring your content so large language models quote it in their answers. A large language model is the software behind tools like ChatGPT, Claude, Gemini and Perplexity. You will also see it called LLMO, or GEO, short for Generative Engine Optimization.
The difference with classic SEO is structural, not cosmetic. Google returns a ranked list of links, and a person scans it and decides what to trust. A language model makes that decision for the person. It reads the sources, picks what it believes, and writes one answer.
So the evaluation work moves from your reader to the model. You are no longer optimizing to be clicked. You are optimizing to be selected and quoted. If you want the mechanics of how a model picks its sources, see how AI search works.
LLM SEO does not replace classic SEO. It sits on top of it. If a model cannot crawl your HTML, read your headings or parse your schema markup, nothing else you do will help. Clean technical SEO is the entry ticket. Clear, well-sourced writing is what wins the citation.
This page is the technical view: what language models do with your text. For the wider strategy, read our guide to AI search optimization. For platform-specific detail, see ChatGPT SEO and Perplexity SEO. To check where you stand today, use the AI visibility checker.
How GEO-Score Helps With LLM SEO
One Check, Four Models
We score your page on the things every major model needs: text it can read, structure it can follow, and claims it can verify. One report covers ChatGPT, Claude, Gemini and Perplexity.
GEO Score Across 22 Metrics
You get one score out of 100, built from 22 separate metrics in four pillars: content quality, AI readiness, technical basis, and authority & trust. You see the score per metric, not just the total.
A Fix List in Priority Order
You get the changes sorted by impact, not a wall of warnings. Answer the question earlier. Add a real statistic. Name your source. Each item says what to change and why it matters.
Why LLM SEO Matters
Work That Keeps Its Value
Search behavior is shifting toward AI-generated answers. The changes LLM SEO asks for — clearer structure, sourced claims, plain writing — also help you in classic search. So none of the work is wasted if the shift is slower than expected.
One Fix, Every Platform
LLM SEO is not tied to one tool. The KDD 2024 study on generative engine optimization tested its methods across several engines and models, and the same improvements held up in all of them. Fix the page once and you gain across ChatGPT, Claude, Gemini and Perplexity.
Evidence, Not Guesswork
The strongest published study on this points one way. In "GEO: Generative Engine Optimization" (Aggarwal et al., KDD 2024), adding statistics, quotations and citations to a page raised its visibility in AI-generated answers by roughly 30 to 40 percent. Our score measures whether your page actually does that.
Start LLM SEO in 3 Steps
Score One Page
Paste a URL into the GEO Score tool. You get a score out of 100 plus a score for each of the 22 metrics. Five page checks per domain are free every 30 days.
Fix the Top Items First
Work down the priority list. Start with the cheap, high-impact ones: answer the main question in the first paragraph, add a real statistic, name your sources, and break long text into clear headings.
Widen It, Then Re-Score
One page is only a sample. A full site audit is €4.99 once, a single-page report unlock is €1.99, and unlimited checks are €29.99 per month. Re-score after each change so you can see what actually moved.
LLM SEO FAQ
What is LLM SEO?
LLM SEO is optimizing your content so large language models quote it in their answers. Those models power ChatGPT, Claude, Gemini and Perplexity. It is also called GEO (Generative Engine Optimization) or LLMO. The goal is to be the source the model picks, not just a link on a results page.
How is LLM SEO different from traditional SEO?
Traditional SEO optimizes for a ranked list that a person scans and clicks. LLM SEO optimizes for a single answer the model writes itself. The judging moves from your reader to the model. In practice that means clear structure, sourced facts and honest writing carry more weight. The two overlap heavily: crawlable HTML, sensible headings and schema markup are still required for either to work.
Which models should I optimize for?
Start with ChatGPT, Claude, Gemini and Perplexity. Those are the four we check by default. You do not need a separate plan for each one. The KDD 2024 research on generative engine optimization tested its methods across different engines and models and found the same content improvements worked in all of them.
How do I optimize a page for language models?
Answer the main question in the first paragraph. Add real statistics and say where they came from. Quote named experts instead of writing "experts say". Use clear headings so a model can find the right section. Add schema markup, and check that AI crawlers are not blocked in your robots.txt. GEO-Score measures all of this across 22 metrics in four pillars: content quality, AI readiness, technical basis, and authority & trust.
Is LLM SEO replacing traditional SEO?
No. It is an extra layer on top. Everything a language model reads still reaches it through crawlable HTML, a sensible site structure and schema markup, which is exactly what classic SEO asks for. What changes is the target. You are writing for a reader that summarizes rather than a reader that clicks.
See How a Language Model Reads Your Page
Get your GEO Score and the full 22-metric breakdown. Five page checks per domain are free every 30 days.
Get Your GEO Score