What is GEO (generative engine optimization)?

Why the term exists

Traditional SEO optimizes for a page of ranked links. Generative engines do something different: they write one answer, name a small number of sources or providers inside it, and most readers never look further. Optimizing for that single generated answer needed its own name, and the field has produced several: GEO, AEO, AI search optimization, LLM SEO. They describe the same work.

Whichever term you use, the unit of success changes. A ranking is a position on a list; a citation is being part of the answer itself. A generated answer might name two or three providers where a results page listed ten, so the work concentrates: fewer winners, more value per win.

What the work actually is

Three layers, roughly in order. First, entity clarity: the engines' picture of who you are, assembled from your site and the web's records about you, has to resolve to one consistent organization with correct basics. Second, answerability: the facts you want quoted, rates, products, eligibility, locations, have to exist as plain text an engine can read and lift. Third, source coverage: the pages engines actually cite in your category have to include you.

The discipline that makes any of it real is measurement: asking the questions your market asks, on the engines your market uses, repeatedly, and tracking whether the answers name you. Generated answers vary run to run, so honest measurement reports how often you appeared, not a single lucky screenshot.

GEO for banking

For local financial institutions the stakes are concentrated in metro-level questions: where should I bank, who has the best auto loan rate, where do I open a business checking account. One generated answer typically names two or three institutions per metro. We measure exactly this for credit unions and community banks, question by question and engine by engine.