LLMO (Large Language Model Optimization)
LLMO (Large Language Model Optimization) is the optimization of content and brand signals to influence how large language models — ChatGPT, Claude, Gemini — understand, remember and cite a company in their answers.
LLMO (Large Language Model Optimization) is the set of actions aimed at influencing how a large language model perceives and represents your brand. It goes beyond page optimization: it works on entity signals — who you are, what you do, who says so — so the model correctly associates you with your areas of expertise.
How LLMO works
An LLM builds a representation of the world from its training data and the sources it consults. LLMO consolidates that representation: consistent definitions in the "X is…" format, original data, repeated brand mentions on trusted sources (YouTube, Reddit, Wikipedia), and E-E-A-T signals. The more consistent and present the entity is, the more confidently the model cites it.
A concrete example
If several independent sources describe an agency as "a GEO specialist in France," the model eventually associates it naturally with that category and suggests it when asked for a recommendation. Consistent off-site repetition does the work.
Why it matters
LLMO acts upstream of the click: it shapes the knowledge the AI has of you. It complements GEO and the building of AI share of voice. To manage it, see our GEO agency.
LLMO isn't won on a single page: it's won across all the signals that define your entity.
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