Generative Engine Optimization (GEO) Agency

Generative engine optimization (GEO) is the practice of getting a brand cited and recommended inside AI-generated answers — ChatGPT, Perplexity, Google AI Overviews and AI Mode, Gemini, Claude and Copilot — rather than ranked as a link. It combines on-site work (crawler access, entity clarity, structured data, answer-first pages) with off-site work (the roundups, directories, articles and Reddit threads the engines quote). The term comes from a 2023 research paper; the practice is what this page describes.

Five things: builds and tracks the list of questions your buyers ask AI assistants; makes your site legible to machines (entity, schema, crawler access); rewrites the pages that decide “recommend” and “how much” answers so the facts are extractable; earns citations in the third-party pages and threads the engines already trust — roundups, directories, articles, Reddit; and reports mention rate, share of voice and citation sources per engine every month. Schema is one of the five, and the smallest. An agency that only does the second and third is an SEO agency with a new page title.

SEO competes for a ranked link on a results page; GEO competes to be the source an AI answer quotes, often with no click at all. They share the foundation — crawlable pages, clear entities, authority — and GEO adds answer-first structure, per-engine tracking and, above all, off-site citations, because in our measurement 63.6% of the sources AI answers cite are pages the brand does not own. GEO does not replace SEO and depends on it: the engines retrieve heavily from pages that already rank and from the third-party pages that rank for “best” and “vs” queries. Keep the SEO; add the citation programme on top. If you already have an SEO agency, we work alongside it.

Answer engine optimization (AEO) aims at being the single direct answer to a question — in an AI answer, a featured snippet or a voice assistant — and leans on FAQ blocks, question-shaped headings and structured data. GEO aims at being cited and recommended across a generated answer that may name several sources, and leans harder on off-site citations and entity clarity. In practice they are one stack with two labels; AI answers pair the two acronyms in the same sentence 62 times in our sample. We run them as one programme and keep a separate AEO page for teams that buy it under that name.

Yes — that is the reason this agency exists in the shape it does. Reddit threads are one of the three off-site surfaces we work (with roundups and articles, and directories and LinkedIn), weighted by what the engines actually cite in your category: in our own category Perplexity quoted a thread in 13 of 31 answers and Google’s AI Overview in 8. Reddit participation runs under the ban-safe policy published on our Reddit marketing page — real, aged accounts belonging to real people who disclose who they work for, each community’s own rules, nothing bought — and it is included from the Programme tier.

Seven: ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Claude and Microsoft Copilot. Three of them — ChatGPT, Google AI Overviews and Perplexity — are tracked daily by our own tracker across every prompt in your set; AI Mode, Gemini, Claude and Copilot are checked by hand every month, because a claim of daily tracking across seven engines would not be true. Each engine retrieves differently (the table above), and the plan is built per engine.

First signals in 2–6 weeks, usually from on-site changes: a restructured page picked up by an AI Overview, a first mention in ChatGPT after the positioning sentence and price go live. Off-site citations compound by month 3–6, as roundup placements, directory profiles and answered threads accumulate and get re-crawled; Reddit placements run on the 4–8 week cycle we publish on our Reddit page. This page is the example: ChatGPT first cited it on 20 September 2026, five days after it went live, while Google’s AI Overview had not cited it by 24 September, because that engine draws on pages that already rank and on roundups. We report against the baseline every month so you see the curve rather than take our word for it.

All three, in that order, and you can see the raw answers. Mention rate: how often each engine names you across your prompt set, collected daily. Citations: which of your pages the engines cite, and your share of voice against your top five competitors. Leads: LLM referral sessions in your analytics, which the engines pass in the referrer or a UTM tag, matched to form fills and pipeline in your CRM. The first two come from our tracker; the third from your analytics, monthly. A screenshot of one good prompt is not a measurement.

The audit is the first two weeks of the programme, and it is free: by day 10 you get your mention rate per engine across 50–200 of your buyers’ questions, the competitors named instead of you and every source the engines cited; by day 15 you get a ranked work plan — which pages to fix and which roundups, directories and threads to earn, in what order. It also covers crawler access, entity and schema. The prompt set, the data and the plan are yours whether or not you hire us.

Because the answer is assembled mostly from pages you do not own: in our 31-question measurement, 63.6% of the citations behind AI answers were other people’s articles and roundups, and only 21.0% were vendor sites. Ranking your own pages gets you into the minority share; being named in the roundups, directories and threads the engines cite gets you into the majority. That is why off-site citations are a core deliverable here, not an add-on.

It is worth it when AI assistants already answer your buyers’ questions with named vendors and you can fund at least a quarter of work — our programme starts at $2,500 a month, month-to-month. If the answers are generic advice with no vendors, it is not worth it yet, and the free audit will tell you which case you are in.

You change what it retrieves: state the correct facts on your own pages in plain sentences, answer or update the old threads as a disclosed person, and get current third-party pages to state the same facts — then re-check the same questions every week. No form makes an engine change what it says about a brand; it re-reads its sources, so the fix is in the sources.

Our GEO programme runs from $2,500 to $7,500 a month, month-to-month, with no minimum term; the tiers above show what each level includes, and the audit that sets the exact number is free. At $4,500 a month — the Programme tier — you get 100 prompts tracked daily across three engines, the baseline audit and source map, up to five pages a month restructured answer-first, roundup and directory placements, disclosed Reddit participation in up to six communities and share of voice against your top five. Across the wider market, quoted GEO retainers cluster around $5,000 a month for mid-market programmes, with entry programmes from about $1,500 and enterprise work from $15,000 up.

No, and nobody honestly can: the engines re-generate every answer, weight sources differently and change retrieval without notice. What we commit to is measurable — the prompt set, the source map, the placements made, the pages shipped — and the report shows whether the mention rate moved. Treat a guaranteed ranking, a fixed number of citations per month or a “cheap GEO package” as the three red flags AI answers themselves warn buyers about.