Generative engine optimization (GEO)
Also known as: GEO
In short
Work intended to improve how content or brands are discovered, represented, and cited in answers produced by generative search systems.
Generative engine optimization (GEO) is a label for work aimed at visibility in generated search answers. It includes making useful information accessible, accurate, and understandable for systems that retrieve and summarize sources.
The original GEO research investigated visibility in generative responses. Its experimental results are not a promise of performance across today’s platforms, topics, or markets.
A practical example
Imagine a merchant publishing an original compatibility guide for replacement vacuum filters. The guide identifies model numbers, explains exceptions, and shows how the information was verified.
The team fixes inaccessible pages and monitors whether relevant answers mention or cite the guide. This illustrative approach gives readers useful evidence while allowing the team to observe outcomes. It does not force an AI system to select the page.
GEO overlaps with established SEO
AEO, GEO, and related labels overlap. Google says its generative search experiences still rely on SEO fundamentals rather than a separate set of mandatory optimizations.
Judge recommendations by the problem they solve and the evidence behind them. Avoid promises of guaranteed citations or fixed rankings inside generated answers. Measure changes using a documented sample, and inspect factual accuracy as well as visibility. More appearances are not useful if the answer misrepresents the product.