Be the answer AI gives.

GEO is the practice of optimizing a brand's content and web presence so that AI engines — ChatGPT, Perplexity, Gemini, Google AI Overviews — cite it, recommend it, and describe it accurately in generated answers.

SEO targets ranked lists of links; GEO targets synthesized answers. They share foundations — authority, structure, content quality — but GEO adds entity optimization, citation engineering, and machine readability. The strongest results come from running both together.

The terms overlap heavily. AEO historically covered featured snippets and voice assistants; GEO refers specifically to generative AI engines. We treat them as one discipline: being the answer, wherever answers are generated.

ChatGPT, Perplexity, Gemini, Microsoft Copilot, Claude, and Google AI Overviews / AI Mode. We benchmark across all of them, then weight effort toward the engines your buyers actually use.

A combination of layers: what the model learned in training, what it retrieves from live web search, how citable and well-structured your content is, how clearly your brand exists as an entity, and how often trusted third-party sources corroborate you. GEO works on every layer, not just your own website.

No — and no honest agency can, because no one controls the output of a model they don't own. What we do guarantee: a measured baseline, a transparent methodology, and monthly reporting on share-of-voice movement. The work is empirical, not magical.

Yes. We track share of voice across a fixed prompt set, citation frequency, sentiment of brand mentions in AI answers, and referral traffic from AI engines — reported monthly in our AI Visibility Score (AVS) framework.

Initial citation improvements typically appear within 60–90 days; durable category-level share of voice builds over two to three quarters, similar to SEO.

Strong organic presence helps, because most engines retrieve from the live web. But it isn't a prerequisite — entity work and third-party presence can move citations while rankings are still building. The two programs compound fastest when run together.

Usually, yes: content restructuring for citability, schema markup, llms.txt, and semantic cleanup. We deliver developer-ready specifications your team can implement, or implement them alongside you.

A plain-text file at your site root that gives AI systems a curated map of your most important content. It's a low-effort, growing-adoption signal — one of several machine-readability standards we implement by default. This site has one.

Volume is smaller than classic organic, but intent is typically higher — a visitor referred by an AI answer arrives pre-qualified by a recommendation. We segment AI referral traffic in analytics so you can see its real commercial value.