Generative Engine Optimization

Generative Engine Optimization (GEO) is the practice of earning visibility inside answers produced by generative AI systems. Instead of ranking a link, you are trying to become a source the model draws on and cites when it composes a response.

GEO vs. AEO

The terms overlap and are often used interchangeably. The useful distinction: AEO focuses on being the extracted answer in answer-engine features (AI Overviews, featured-snippet-style results), while GEO focuses on being represented and cited across generative systems more broadly — including chat assistants that synthesize from many sources and may not surface a traditional SERP at all.

Both reward the same foundations: clear, well-structured content; strong entity and topical signals; authoritative sourcing; and being present in the indexes and training-adjacent data these systems retrieve from.

Example

Ask an AI assistant “which paper is best for high-volume office printing,” and a generative engine assembles an answer from several pages. A brand that publishes a clear, well-structured buying guide — with named products, attributes, and plain comparisons — is far likelier to be pulled in and cited than one whose advice is locked inside images, PDFs, or JavaScript-gated tabs.