Getting AI assistants to name your brand when someone asks what to choose. Generative engine optimization (GEO), answer engine optimization (AEO) and AI search optimization are three names for that same job — the field has not settled on one yet, and we use them interchangeably here.
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Google ranks pages. An assistant names brands. There is no fourth place in an answer — your name is in it or it is not, and the person asking rarely goes looking for a second opinion.
The other difference matters more. An assistant does not open your homepage to decide whether to recommend you. It repeats what it already read elsewhere, in sources it has learned to trust. Which means the most important pages for your visibility are pages you do not own.
A brand absent from these does not get named, however good the product is. This is the part founders underestimate: the work is mostly outside your own site.
Competitors appear in the reviews and comparisons the assistant cites. You do not. Nothing you publish on your own domain substitutes for that.
Your pages do not answer the questions buyers ask in a form a model can lift and quote. Marketing copy reads well to people and gives a model nothing to repeat.
The model is not sure what the product is or who it is for, so it does not risk naming it. Recommending the wrong thing costs an assistant more than saying nothing.
In rough order of how much it moves the number:
Get into the comparison content of your category. A mention by someone else outweighs anything you write about yourself. Find the roundups that already rank for your category and get considered for them.
Say in one plain sentence what you do and who for. Put it where a crawler meets it first — title, first paragraph, structured data. A model that cannot classify you will not recommend you.
Answer the real questions, in question-and-answer form. Not a blog post that circles the topic — the question as a heading, the answer directly under it.
Keep the naming consistent. One spelling, one description, everywhere. Every variant splits the evidence a model uses to decide you are worth naming.
“We seem to come up more often” is not a measurement. Ask the engines the questions your buyers actually ask, count how often your name comes back, then repeat the same questions after the change.
We ask ChatGPT and Gemini the buying questions from your niche and count how often they name you — with the margin of error, and with the competitors named instead. Free, no card.
Two engines, three questions, no card.
SEO gets your page ranked. GEO and AEO get your brand named. Search returns a list of links and you can be fourth; an assistant returns a handful of names and you are either in them or you are not. The work is also aimed elsewhere: SEO changes your own pages, GEO changes what other sources say about you.
Weeks to months. Assistants do not re-read the web on every question — they answer from a view of it that refreshes slowly. A change to your own site can show up quickly; getting into the comparison articles and review pages the models trust takes longer, because someone else has to publish it.
No. Schema helps a machine parse a page it already has. It does not put your name into a roundup someone else wrote, and roundups are where most recommendations come from. Markup is worth doing and it is not the lever.
Today, the ones people actually ask for recommendations: ChatGPT and Gemini. The practice does not change per engine — they draw on overlapping sources and reward the same things.