Generative Engine Optimization services that make AI recommend you

GEO stands for Generative Engine Optimization. It’s the practice of making a brand visible, trusted and citable inside AI-generated answers — the responses produced by ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews. Where SEO optimises for a ranked list of links, GEO optimises for being named, quoted and recommended in the answer itself. It’s also called answer engine optimization (AEO), AI search optimization or LLM SEO. Note that GEO here means generative engine optimization, not geographic or geo-targeting.

SEO aims to rank a page in a list of blue links so a user clicks it. GEO aims to get your brand named and cited inside a generated answer, where there may be no list and often no click at all. The success metric differs: SEO is measured in rankings, impressions and sessions; GEO is measured in citation share across AI engines, how often you’re named versus a competitor, and AI-referred traffic.

The tactics overlap but aren’t identical. SEO leans on keyword targeting, link acquisition and technical health. GEO leans on entity clarity, structured data, extractable content formatting, conversational query coverage and third-party corroboration.

Yes. GEO builds on SEO foundations rather than replacing them. AI engines still draw heavily on crawled and indexed web content, so if a page can’t be crawled, rendered or understood, it can’t be cited either. Technical health, clean site architecture and genuinely useful content remain prerequisites.

We treat them as one service for exactly this reason. Splitting them is what produces the gap most brands are stuck in: decent rankings, invisible in AI answers.

Months, and it compounds. Some technical and schema fixes register within weeks — an engine picking up a corrected entity description, for example. But meaningful movement in citation share generally takes three to six months, because it depends on content being crawled and re-crawled, third-party corroboration accumulating, and model providers refreshing their retrieval sources.

Anyone promising you a fixed timeline to a fixed AI citation position is guessing. AI answers are also genuinely volatile: the same prompt can return different sources week to week, which is why we measure with a fixed prompt set on a fixed cadence rather than reacting to one-off screenshots.

We build a fixed prompt set — typically 30 to 50 buying-intent questions from your category — and run it across each target engine on a set cadence. For every run we record whether your brand is named, whether it’s named first or in passing, whether your domain is linked as a source, and which competitors appear instead.

Alongside that we track AI-referred sessions by referrer, and branded search impressions and clicks in Search Console. Same prompts, same engines, same method every time, so the numbers are comparable. We publish the methodology with the numbers — a citation-share figure without a stated prompt set and date range doesn’t mean anything.

Primarily ChatGPT, Perplexity, Google Gemini and Google AI Overviews, with Claude and Microsoft Copilot covered where they matter to your audience. The underlying work is largely shared — entity clarity, structured data and citation-ready content help across all of them — but retrieval behaviour differs by engine, so we report per engine rather than as a single blended score.

Yes, though the shape of the work differs. For DTC and ecommerce, buyers ask AI engines for product and brand recommendations, so the emphasis falls on product entity data, category content, review and comparison corroboration. For SaaS and B2B, the questions are more comparative and solution-led (“best tool for X”), so category positioning, comparison content and directory presence carry more weight. For SMBs, the same mechanics apply at a smaller scale: fewer buyers are asking, but the citation set is usually thinner and easier to enter.

What doesn’t change: if your category has buyers asking AI engines what to choose, there is a citation set, and you’re either in it or you aren’t.

Thirty minutes, straight to the substance: how AI engines choose the brands they name in your category, an honest read on whether your site is citable as it stands, where GEO would move something for you first, and what a sensible first ninety days would look like. You also get a plain explanation of how AI visibility is measured, so you can judge any GEO proposal — ours or anyone else’s.

No cost and no commitment. If GEO is the wrong spend for you right now, you will hear that on the call: book your consultation call here.