LLM Optimisation (LLMO)

LLM optimisation (LLMO) is the practice of making your brand and content easier for large language models to understand, retrieve and mention accurately in their answers. It overlaps heavily with SEO, answer engine optimisation and generative engine optimisation, but focuses on how AI assistants learn about and describe you.

Written by Paul Hoda, SEO consultant since 2005. Last updated 8 November 2026.

What LLM optimisation means

A large language model (LLM) is the type of AI behind tools such as ChatGPT, Gemini, Claude and Copilot. These tools can talk about your business in two ways: from what the model absorbed during training, and from pages it fetches live when answering a question. LLMO aims to improve both.

The term is used loosely. Some people treat it as a synonym for generative engine optimisation. Others use it more narrowly for influencing what models "know" about a brand. In practice the tactics are almost the same.

How it relates to traditional SEO

Most AI assistants that browse the web rely on a search index to find sources. ChatGPT search, Perplexity and Copilot all retrieve pages before writing an answer, and Google’s AI features draw on Google’s own index. That means the basics still apply:

  • Pages must be crawlable and indexable.
  • Content must clearly answer real questions.
  • Your site needs authority signals such as links and mentions.

LLMO adds an extra layer: making sure facts about you are consistent everywhere, so a model building a picture of your brand finds the same story on every source.

Practical ways to improve LLM visibility

  1. Allow the right AI crawlers in robots.txt if you want to appear in AI answers.
  2. Write clear, self-contained sections that state facts plainly, so a passage still makes sense when quoted on its own.
  3. Strengthen your brand entity with consistent names, descriptions and details across your site, profiles and directories.
  4. Earn mentions on trusted third-party sites, reviews and forums, since models often lean on independent sources.
  5. Publish original data, expert opinion and specifics that other pages do not have.
  6. Use structured data to describe your organisation, products and people.

How to measure it

There is no official ranking report for LLMs. Common approaches include running a fixed set of prompts regularly and recording whether you are mentioned or cited, a method often called prompt tracking. You can also watch referral traffic from AI tools in your analytics. Answers vary between users, sessions and model versions, so look at trends over time rather than single results.

Common myths

  • Myth: there is a secret LLM ranking trick. No provider has published a ranking formula, and claims of guaranteed AI placements should be treated with caution.
  • Myth: special files guarantee inclusion. Proposals such as llms.txt are not a confirmed ranking or citation signal for the major assistants.
  • Myth: SEO no longer matters. Retrieval still depends on search indexes, so strong SEO remains the foundation.

For help getting your brand cited in AI answers, see my work as an AI SEO consultant.

Key Takeaways

  • LLM optimisation aims to help AI assistants understand and mention your brand accurately.
  • AI tools learn from training data and from pages they retrieve live.
  • Strong technical and content SEO is still the foundation of LLM visibility.
  • Consistent facts and trusted third-party mentions strengthen how models describe you.
  • Measure with repeated prompts and AI referral traffic, looking at trends rather than single answers.

Related Terms

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