What Is LLM SEO? A Plain-English Guide

LLM SEO is the practice of making your website and your organisation easy for large language models, such as the ones behind ChatGPT, Claude, Gemini, Copilot and Perplexity, to find, understand and cite. It covers two routes: what a model learns about you during training, and what it reads when it searches the web before answering. In practice, LLM SEO is another name for generative engine optimisation (GEO), with answer engine optimisation (AEO) as the page-level part of the same job.

The term is useful because it names the reader you are writing for. A large language model is a new kind of visitor. It does not click, scroll or look at your design. It reads text, pulls out facts and decides whether your page helps it answer someone else’s question.

How does LLM SEO relate to GEO and AEO?

The labels overlap, and different agencies use them differently.

• GEO, generative engine optimisation, is the most common name for getting your organisation named and recommended in AI answers. If you have also seen “GEO” used for local SEO, GEO SEO explained clears that up.
• AEO, answer engine optimisation, is about a specific page being quoted as the answer to a specific question.
• LLM SEO describes the same territory from the machine’s side: what the model reads, how it reads it, and what makes it trust a source.

Google’s view is worth knowing. Its guide to optimising for generative AI features says that, from Google Search’s perspective, optimising for AI search is still SEO, and it warns against “hacks” sold under new names. That matches our experience: the foundations have not changed, but there is extra work on top.

What do large language models actually read?

There are two quite different moments when a model “reads” your website, and they need different thinking.

At training time

Models learn from very large collections of public text gathered months or years before you use them. If your organisation was described clearly and often across the web before that cut-off, the model has a picture of you. If it was not, the model knows little or nothing, and may guess.

You cannot submit pages for training. You can only allow or block the training crawlers, and make sure what is written about you, on your site and elsewhere, is accurate.

At answer time

For questions about current providers, prices or recommendations, most assistants now search the web before answering. This is called retrieval or grounding. The assistant runs one or more searches, fetches a handful of pages, picks out the passages that answer the question and writes its reply with links.

This is the route you can influence quickly, because it depends on whether your pages are crawlable, indexed by the right search system and written in passages worth quoting.

	Training	Retrieval
What happens	The model learns from text collected before its cut-off	The assistant searches and reads pages live
Example crawlers	GPTBot (OpenAI), ClaudeBot (Anthropic)	OAI-SearchBot (ChatGPT search), Claude-SearchBot, PerplexityBot, Bingbot for Copilot
How fast changes show	Months, at the next model update	Days to weeks, once pages are recrawled
What you control	Crawler access and what is written about you	Crawler access, indexing, page content and structure

OpenAI documents its crawlers separately in its overview of OpenAI bots, and the settings are independent: you can block GPTBot from training and still allow OAI-SearchBot so you appear in ChatGPT search.

Seven practical steps for LLM SEO

Our guide to getting recommended by ChatGPT covers the business side: reviews, directories and consistent details. These steps focus on the website itself.

1. Check which AI crawlers can reach you

Open yoursite.com/robots.txt and look for rules naming GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot or a blanket Disallow: /. Then check your CDN or security plugin, because some block AI crawlers by default or with a single toggle. Decide deliberately which search crawlers you allow; blocking them removes you from those assistants’ live answers.

2. Put your content in the HTML

Googlebot renders JavaScript. Many AI crawlers fetch the raw HTML and may not. Load a key page with JavaScript switched off, or use “view source”, and check that the main text, prices and contact details are there. Content that only appears after a script runs, inside tabs that load on click or inside images, may be invisible to them.

3. State facts as plain sentences

Models extract facts. “Kickass Online is a UK web, SEO and AI agency working with membership bodies and professional services firms” is a fact a model can store and repeat. “Bold digital thinking for ambitious brands” is not. Put who you are, what you do, for whom, where, and from what price in plain sentences on your homepage, about page and service pages.

4. Write passages that survive being lifted out

Assistants quote passages, not pages. Each paragraph should name its subject and carry its own detail. “Our care plan includes daily off-site backups” works alone. “It also includes these” does not.

5. Cover the follow-up questions, on the same page

When an assistant answers a question it often runs several related searches in the background. Google calls this query fan-out. A service page that also answers cost, timescale, eligibility and “how is this different from X” gives the assistant more reasons to use it. Do this within one good page. Google is explicit that spinning up separate pages for every variation of a query, to manipulate AI answers, breaches its scaled content abuse policy.

6. Make it easy to identify you

Use the same organisation name everywhere, add Organization schema with links to your official profiles, and keep an llms.txt file if you want a plain summary for tools that read one. Google says its search ignores llms.txt, so treat it as optional housekeeping, not a lever.

7. Test what the models say

Ask two kinds of question. A brand question (“What does [your organisation] do?”) shows what the model knows or finds about you. A category question (“Who are the best [service] providers in [area]?”) shows whether you are recommended. Run both in each assistant with web search on, note the sources cited, and repeat monthly with the same wording.

What LLM SEO will not do

It will not get a weak business recommended. Models reflect what is written about you, and if few independent sources mention you, no amount of on-page work changes that. It will not work overnight for memory-based answers, because those wait for the next model update. And nobody can guarantee a mention, because the assistants decide what they cite.

Where to start

Do steps 1, 2 and 7 this week: check your robots.txt and CDN settings, view your key pages without JavaScript, and ask three assistants what they know about you. That tells you whether you have a technical problem, a content problem or a reputation problem.

If you want it done properly, our GEO service covers the technical access, the rewriting and the monthly prompt tracking, with page-level AEO in the same retainer.