What is Generative Engine Optimisation (GEO)?

Why does GEO matter now?

Because the loss is invisible. When an assistant recommends three suppliers and you are not among them, there is no impression, no bounce and no line in your analytics. The enquiry simply goes elsewhere, which is why most businesses notice this late.

A normal ranking drop announces itself. Traffic falls, the dashboard turns red, somebody investigates. An absence from AI answers does none of that. The buyer asks a question, receives three names, contacts one of them, and you never learn the conversation happened.

That asymmetry is the whole argument for acting early. The businesses being recommended today are not necessarily the largest ones. They are the ones whose information is structured clearly enough for a model to read, trust and repeat.

How is GEO different from SEO?

SEO competes for a position in a list of links. GEO competes to be part of the answer itself. SEO gets you found, AEO gets your answer extracted into a snippet, and GEO gets your business named in a recommendation. They share technical foundations but differ in what they win.

The practical consequence is that you should not treat these as three sequential projects. The technical work overlaps heavily: clean page structure, schema markup and unambiguous entity definition serve all three simultaneously. What differs is the content strategy layered on top.

• SEOSomeone searches, and you appear in the results.
• AEOSomeone asks a question, and your answer is the one quoted above the results.
• GEOSomeone asks an assistant for a supplier, and your business is named.

What does GEO work actually involve?

Three things: making your entity unambiguous, making your site machine readable, and earning mentions elsewhere. Models resolve who you are before they weigh any keyword, so consistency across your own site and third party sources does most of the work.

Entity groundwork comes first. Your name, category, location and description should be identical everywhere they appear: your site, your schema markup, your Google Business Profile, your directory listings and your social profiles. Contradictions lower a model's confidence, and low confidence means exclusion rather than a wrong answer.

Machine readability comes second. Structured data tells a system what kind of organisation you are and what each block of text represents. An llms.txt file at your site root gives assistants a plain summary to read at inference time rather than inferring your business from scattered fragments.

Third party mentions come third, and they matter most. Assistants weight what others say about you more heavily than what you say about yourself. One credible industry mention outperforms a page of your own claims.

How do you measure GEO?

By running prompts, not by reading a dashboard. Agree the questions your buyers would realistically ask, run them monthly across the major assistants, and record whether you appear, how you are described, and who appears instead of you.

There is no equivalent of rank tracking yet, and any vendor presenting a precise GEO score is describing a proxy rather than a measurement. Direct observation is the honest method and it is checkable by anyone in the room.

Take a baseline before the work starts. Without it you have no way to distinguish improvement from the natural variance of a model refreshing its view of the web.

How long does GEO take to work?

Slower than SEO. Technical corrections can register within weeks, but assistants refresh their picture of the web on their own schedule, so meaningful movement in citations typically takes months rather than days.

Anyone promising rapid AI visibility is either describing paid placement or misunderstanding how these systems retrieve information. Treat the work as compounding rather than immediate, in the same way sound SEO compounds.