GEO and AEO: How to Get Your Brand Mentioned by ChatGPT, Gemini and Perplexity

For twenty years, search marketing had one question: how do I get my site onto the first page? Now there is a second question of equal weight: how does my brand get named when someone asks an AI?

The difference is not merely terminology. In classic search the user sees ten links and chooses. With an AI assistant the user receives one answer that has already chosen for them — usually naming two to four options. If your brand is not among them, you are not ranked eleventh; you are simply absent from that conversation.

These do not replace one another. In practice they reinforce each other, because the sources that make you strong in one place usually make you strong in the others.

This is the most misunderstood part. Models do not choose based on how good your website is. They choose based on how often and how consistently your brand appears across the sources they read.

1. Write pages that answer one specific question completely. Models cite what is quotable, and what is quotable is a clear answer rather than a warm-up paragraph.
2. Publish honest comparison pages, including where your product is not the best choice. Such content gets cited more often precisely because it reads as judgement rather than advertising.
3. Make your business name, category and description consistent everywhere. Models build understanding from repetition; inconsistent naming fragments the signal.
4. Collect reviews regularly and ask for context. A review saying “fast and accurate on wholesale orders” is far more useful to a model than five stars with no text.
5. Fill in listings on directories relevant to your category, not general directories containing every kind of business.
6. Add structured data and a question-and-answer page. This helps engines understand which entity you represent and which questions you answer.

It is tempting to assume every old practice is now obsolete. It is not. Page speed, clean heading structure and content that genuinely answers the question remain the foundation — because AI engines still read the web, and pages that are hard for humans to read are usually poor in signal for machines too.

What has changed is the weighting. You used to compete for position. Now you also compete to be named, and that is decided by your trail across the whole web rather than by a single page.

The most real problem in this work is measurement. There is no visible ranking inside an AI answer, and asking one prompt once then drawing conclusions is unreliable — models can answer the same question differently on different attempts.

What is reliable is repeated sampling: asking the same prompt many times across several engines, then counting what share of answers name your brand, in which position, and in what tone. Only then can trends be read and the impact of your work be demonstrated.