Generative engine optimization (GEO): what it is and how to do it

Generative engine optimization (GEO) is the practice of improving how often and how favourably generative AI systems, like ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews, mention your brand in their answers. The term came from academic research in 2023 and is now a standard line item in marketing plans.

Why GEO matters now

Buyers increasingly ask an assistant for a shortlist instead of searching and clicking ten results. If the assistant names three tools and you are not one of them, you lose the deal before it starts, and your analytics never show it happened.

How GEO differs from SEO

• Output: SEO earns a ranking position. GEO earns a mention, a position in a list and a tone.
• Signals: SEO leans on links and on-page relevance. GEO also leans on how often trusted third-party sources mention you.
• Measurement: SEO has Search Console. GEO needs prompt tracking across models, because there is no official data.

Core GEO tactics

• Track the prompts that matter and the sources each model cites for them.
• Earn mentions on those sources: reviews, comparison articles, community threads, documentation.
• Publish clear, fact-dense pages for pricing, comparisons and use cases.
• Keep your brand facts consistent everywhere so models do not mix you up.
• Monitor sentiment, because being mentioned negatively can be worse than not being mentioned.

Measuring GEO

GEO metrics start with visibility (how often you appear), position (where in the answer) and sentiment. The metric most teams miss is the business result: how much traffic and revenue AI answers send. StatSip tracks all four, so GEO can be judged like any other channel.

• Answer engine optimization guide →
• Putting a dollar figure on AI search →
• See StatSip pricing →