The term GEO was popularized by a 2023 academic paper that measured how content changes affect visibility in generative engine responses. Since then it has become one of the umbrella names, together with AEO and LLMO, for the work of earning presence in AI-generated answers.
GEO versus classic SEO
Classic SEO optimizes a page to rank in a list of links. GEO optimizes a brand's evidence so that generated answers describe and recommend it correctly. A company can rank well and still be absent from AI answers if its facts are ambiguous or third-party sources do not support its claims. The two disciplines share the technical foundation: crawlable, fast, well-structured pages remain a prerequisite.
- Unit of optimization: the generated answer, not the ranked page.
- Key signals: verifiable claims, consistent entity data, citations from trusted sources.
- Measurement: repeated prompt sampling and share of voice, not ranking positions.
- Output: being named, described accurately, cited and recommended.
In practice GEO, AEO and LLMO describe overlapping work, and most providers use the terms interchangeably. What matters is whether a program measures answers statistically and improves the legitimate evidence behind them.