LLM SEO, how to optimize for large language models

LLM SEO, also called LLM optimization or LLMO, is the work of making your content and brand easy for large language models to find, understand and repeat accurately. LLMs reach your business in two ways: through what they absorbed in training, and through pages they fetch live when a tool like ChatGPT search, Perplexity or Google's AI Mode looks something up. LLM SEO improves both by making pages retrievable, writing passages that stand on their own, keeping your facts consistent across the web and getting mentioned on sources the models lean on.

LLM SEO, GEO and AEO describe largely the same work from slightly different angles. Our explainers on GEO and AEO cover the definitions. This post focuses on the mechanics: how a language model actually ends up using, or ignoring, your content.

How does a language model find your content?

Through training data

A model learns patterns from a very large snapshot of text collected before training. If your company was described often and consistently on the web before that snapshot, the model is more likely to know who you are and what you do. If you were barely mentioned, it may know nothing, or guess.

You cannot update this quickly. It changes when a new model version is trained. What you can do is make sure that, over time, the web says clear and consistent things about you.

Through live retrieval

Most AI search products now look things up when a question needs current or specific information. The general pattern is often called retrieval-augmented generation: the system turns the question into one or more searches, fetches a set of pages, picks the most relevant passages, and writes an answer from them, often with citations.

Google has described a technique it calls query fan-out for AI Mode, where one question is broken into several related searches run at once. Other systems work in similar ways. The practical effect is that your page can be pulled in for a sub-question you never targeted directly, as long as it ranks and answers that sub-question clearly.

This path changes fast. A new or updated page can be retrieved within days of being indexed.

How is LLM SEO different from Google SEO?

The overlap is large. Retrieval often starts from search results, so pages that rank well in Google and Bing are more likely to be pulled in. LLM SEO builds on SEO rather than replacing it.

What makes a passage easy for an LLM to use?

When a retrieval system splits your page into chunks and picks the best ones, each chunk is judged largely on its own. That favors writing where every section makes sense without the rest of the page.

• Open each section with the answer, then explain. A heading like "How long does order entry automation take to set up?" followed by a direct first sentence gives the system a clean passage.
• Name things fully. "Our platform" means nothing out of context. "Dravik's business audit" or "the ERP integration" does.
• Define terms where you use them, in one sentence.
• Put numbers next to their source. "According to the US Bureau of Labor Statistics" travels with the figure. A statistic with no source is easy to ignore or misquote.
• Use tables for comparisons and numbered lists for steps. Structured content survives chunking well.
• Avoid relying on images or interactive widgets for key facts. Models mostly read text.

Our guide to writing content AI engines quote has more examples.

Why does consistency matter so much for LLMs?

A language model builds its picture of your business from everything it reads. If your website says you serve "mid-market manufacturers", your LinkedIn says "SMBs", a directory lists you under the wrong category and an old press release names a service you dropped, the model's summary will be vague or wrong.

Fix this with one standard description of what you do, who you serve and where, used on:

• Your homepage and About page
• LinkedIn and other social profiles
• Google Business Profile, Bing Places and Apple Business Connect
• Industry directories and review sites
• Partner and association listings

Structured data helps too. Organization markup with your name, URL, logo and sameAs links to your official profiles gives machines an unambiguous reference point. See our schema markup guide.

Which sources do LLMs lean on?

When AI tools answer questions about providers or products, they frequently cite sources other than brand sites: review platforms, directories, industry publications, comparison articles, Wikipedia, Reddit and YouTube. Which ones depends on the industry.

To find yours, ask the main AI tools the questions your buyers ask and record which domains are cited. Then make sure you are present and accurately described on the ones that recur. Our post on the sources AI engines trust goes deeper, and brand mentions in AI search explains why unlinked mentions still count.

What technical work does LLM SEO need?

• Allow the crawlers you want. OpenAI, Perplexity, Anthropic and Google document their crawlers and how to control them in robots.txt. Our post on AI crawlers and robots.txt explains which do search retrieval and which collect training data, so you can choose separately.
• Serve content in HTML. Not every crawler renders JavaScript fully.
• Keep pages fast and stable so fetches succeed.
• Keep pages indexed in Google and Bing.
• Show clear published and updated dates.

An llms.txt file is often sold as essential for LLM SEO. No major AI provider has confirmed using it for answers, so treat it as optional. See llms.txt explained.

How do you measure LLM SEO?

You cannot see inside the model, so measure the outputs:

1. Keep a fixed list of buyer questions.
2. Run them monthly in ChatGPT with search, Perplexity, Gemini, Copilot and Google.
3. Record mentions, citations, accuracy of the description and competitors named.
4. Track AI referral traffic in analytics (see measuring AI search traffic).
5. Add an "AI assistant" option to your "how did you hear about us" field.

Tools can automate the checks; our overview of AI visibility tools compares the types.

What are LLM SEO services, and do you need them?

An LLM SEO service usually bundles a visibility baseline, technical fixes, content rewrites, off-site work on the sources that matter and monthly measurement. It is worth paying for when buyers in your market research with AI tools before contacting anyone and you lack the time or skills in-house. Our guide on how to choose an AI SEO agency lists the questions to ask.

The AI search visibility page explains how Dravik handles this for US businesses with up to 500 people. If you want to see how language models currently describe your business, book a business audit: $199, fixed price, a 30 minute call plus a written plan, with a full refund if it is not worth it.