Generative Engine Optimization (GEO)
Generative engine optimization (GEO) is the wider practice of getting AI systems to describe and suggest your brand accurately, across whatever a shopper asks. Where AEO chases a single cited answer, GEO is about the whole impression a model carries of your brand.
How it works
GEO is the wider version of answer engine optimization. AEO is mostly about earning a citation inside a direct answer; GEO is about the whole picture of how a generative system describes you, whether the shopper asked a question, asked for a recommendation, or compared options. In practice the two terms overlap, and some people use them interchangeably. Both come down to being indexed, readable, and clear enough for a model to represent you accurately.
A commerce example
If an assistant, asked to compare running shoe brands, describes your shoe with the wrong material or an old price, that is a GEO problem: the model's picture of your product is stale or incomplete. Complete, current structured data and pages that are actually crawlable are what keep that picture accurate.
What this means for your store
You cannot control what a model says, but you control what it reads. Keep your product data complete and current, stay indexed in both Google and Bing, and fix the pages an assistant is most likely to pull from. See how to get your products recommended by AI.