Generative engine optimization

What it means in practice

The two labels are used interchangeably by most practitioners. Where people do draw a line, GEO is framed around generative assistants such as ChatGPT and Gemini, and AEO around answer features inside traditional search such as AI Overviews and featured snippets. The distinction is not stable enough to plan around, and neither term describes a measurement method. Whichever label a vendor uses, the question worth asking is what they observed, how many times, and whether you can see the answer behind the number.

How refd treats it

This is category vocabulary, not a refd metric. refd measures what AI answers actually said across repeated runs, and publishes the raw answer behind every number. Where a term above carries a claim about what causes visibility, refd treats that claim as a hypothesis to test rather than a setting to configure.

This definition is editorial. It describes how the term is used across the field rather than something the software computes, so unlike the metric pages it is not generated from the product.