Generative engine optimization (GEO)

Generative engine optimization is a term used interchangeably with answer engine optimization for the practice of improving how a brand appears in AI-generated answers. GEO originates from a 2023 academic paper by Aggarwal et al.; AEO is the term more common in industry.

The distinction is mostly one of origin rather than substance.

GEOAEO
Coined inAggarwal et al., 2023 (arXiv)Marketing practice, by analogy with SEO
Used byResearch literatureAgencies, vendors, in-house teams
The work it namesGet cited in generated answersGet cited in generated answers
The terms differ in where they came from. The bottom row is the one that decides whether a distinction is worth paying for — and it is the same row twice.

“GEO” entered use through GEO: Generative Engine Optimization (Aggarwal et al., 2023), which tested which content changes increased a source’s visibility in generative search responses. “AEO” grew out of marketing practice, by analogy with SEO.

The two terms have since converged in ordinary use. Practitioners say AEO; the research literature says GEO.

Vendors sometimes claim a technical difference — that GEO covers content optimisation and AEO covers structured question-and-answer formatting, or the reverse. We are not aware of a stable industry definition that supports the split. Treat any pitch that leans on the difference between the two with suspicion.

We use AEO because “answer” describes the artefact we are trying to appear in.

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