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Glossaire · GEO

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.

Key takeaway

LLMO isn't won on a single page: it's won across all the signals that define your entity.

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