Generative Engine Optimization (GEO)

Full definition

Generative Engine Optimization (GEO) is the term used interchangeably with Answer Engine Optimization (AEO). Coined by Princeton researchers in 2023 in their seminal paper on optimizing for generative AI search, the term emphasizes the generative nature of modern AI search interfaces. GEO techniques include: high-density factual content in the first third of pages, explicit citations and statistics within the text, structured data (Schema.org), freshness signals, content depth over keyword density, and entity disambiguation via Schema.org @id URIs. Platforms differ in citation rates: Perplexity cites sources in 97% of cases, Google AI Overviews 34%, ChatGPT 16% (Otterly 2025 data).

Examples

• ·Refactoring a product review to put the verdict in the first paragraph (rather than the conclusion) for higher GEO citation rates.
• ·Adding statistics with named sources within the body of an article rather than only in references.
• ·Using Schema.org @graph with stable @id URIs to help LLMs build a coherent knowledge graph of your site.

See also

• Answer Engine Optimization (AEO)
• Large Language Model (LLM)
• Schema.org Markup