What generative engine optimization means in practice
Generative engine optimization is the work of shaping what AI systems say when buyers ask about your category. Instead of competing for a position in a list of links, you compete for a place in a written answer, often a shortlist of three to five brands with a sentence on each. Our generative engine optimization services focus on three questions: are you mentioned, are you cited, and is what the AI says about you correct?
GEO is one part of our wider AI SEO services. It shares foundations with classic SEO, but it adds its own research method, content standards and metrics.
Where the term GEO comes from
The term was introduced in a 2023 research paper by academics from Princeton University, Georgia Tech, the Allen Institute for AI and IIT Delhi. They built a benchmark of queries, ran them through a generative search setup and measured how content changes affected visibility in the answers. Adding statistics, quotations and citations to credible sources tended to help, while keyword stuffing did not.
Research settings are not production systems. We treat those findings as hypotheses to test on your prompts, not as rules.
How prompt mapping works
Keyword research tells you what people type into Google. Prompt mapping tells you what they ask an assistant, which is usually longer and more specific. “CRM software” becomes “best CRM for a 20-person real estate team that works with Gmail.” Every added constraint changes which brands get named.
We build a fixed panel of these prompts from your search data, sales and support conversations, and community threads. Each prompt is tagged by funnel stage and mapped to the page that should answer it. We then run the panel across ChatGPT, Perplexity, Gemini, Copilot and Google AI Overviews several times each, because answers vary between runs.
The output is a citation gap map. It shows which prompts you win, which you lose, which sources the engines rely on instead and what those sources say. That map drives every recommendation that follows.
What makes a source citable
Three properties keep showing up in the pages AI engines cite. We audit every priority page against all three before recommending changes.
Retrievable
The page is indexed in the search indexes the engine uses, loads fast and serves its main content in HTML rather than behind JavaScript. This part is well documented. If a crawler can’t fetch the page, it can’t be a source.
Trustworthy
The brand behind the page is a clear, consistent entity, and other reputable sites mention it. Models appear to weigh what the wider web says about you. That is why reviews, trade press and community discussions carry so much weight in GEO.
Quotable
The page states answers plainly near the top of each section, with specifics a model can lift: a number, a definition, a named method or a comparison. Vague marketing copy gives a model nothing to cite.
The off-site half of GEO
For recommendation prompts, the cited sources are often not brand websites at all. They are comparison articles, review platforms, Reddit threads, YouTube videos and industry publications. Earning accurate, favorable mentions there is often the fastest route into the answer, and our link building and digital PR team targets the exact domains your citation gap map surfaces.
What a good GEO agency won’t do
We don’t use hidden text, prompt-injection tricks or fake reviews. We also don’t mass-produce thin “best of” lists that rank our clients first. These tactics may move an answer briefly, but they risk penalties in Google and erode the trust that makes AI engines cite you in the first place.
Who GEO is for
GEO pays off fastest for brands whose buyers research before contacting sales. That includes professional services firms, e-commerce brands in considered categories and multi-market businesses. See where you stand today with a free AI visibility audit.