LLMO (Large Language Model Optimization)
LLMO is the discipline of optimising content and technical configuration so that LLMs (ChatGPT, Claude, Gemini, Perplexity) use and cite your brand and information in their answers.
LLMO overlaps heavily with GEO but emphasises the training and in-context side: how do you ensure your brand is mentioned in an LLM answer, even when no real-time search is involved. Tactics: strong brand mentions on authoritative sites, structured definitions (Wikipedia, Wikidata), clear homepage positioning, a /llms.txt file, consistent facts about your product/service.
Example
Webrock Media wants to be named when someone asks ChatGPT 'best GEO agency Netherlands'. Strategy: content on GEO on own domain, guest articles on Frankwatching and Emerce (brand mentions), Wikidata entry with consistent description, /llms.txt file.
Frequently asked questions
LLMO or GEO — what's the difference?
GEO (Generative Engine Optimization) focuses on generative search engines (AI Overviews, Perplexity). LLMO focuses more broadly on LLMs themselves, including ChatGPT without search. ~70% overlap.
Can I measure LLMO?
Partially. Tools like Profound, Otterly, Peec AI and custom prompts measure how often your brand appears in LLM answers to relevant questions. Frequency tracking is a young discipline.
Related terms
Further reading
- → Our service: GEO