What is generative engine optimization (GEO)?

Where the term comes from

GEO was defined in the paper “GEO: Generative Engine Optimization,” presented at the ACM SIGKDD conference (KDD 2024) by Aggarwal and colleagues.1 The authors also released GEO-bench, a benchmark of thousands of real queries across domains, so different optimization strategies can be measured rather than guessed at.2

How GEO differs from SEO

Classic SEO tries to make a page rank near the top of a link list. GEO tries to make a passage get quoted inside a generated answer.1 The unit of success shifts from position on a results page to inclusion and attribution in the answer itself — which means optimizing at the passage level, not just the page level.

What actually works

The study tested many tactics. The ones that reliably increased visibility were adding relevant statistics, direct quotations, and credible citations, plus clearer, more fluent writing.1 Notably, keyword stuffing — the old SEO reflex — did little to help in generative answers. In other words, the winning move is to make content genuinely more authoritative and quotable.

Is GEO just gaming the AI?

It can be misused, but the healthy reading is the opposite: the tactics that work are the same ones that make content trustworthy for humans — real data, honest sourcing, and clarity. That also connects to a known weakness of answer engines: studies show generated answers sometimes cite sources that don’t fully support the claim.3 Well-sourced, verifiable pages are both good GEO and good citizenship. (See what is an answer engine?)