GEO & AI Search
What is Generative Engine Optimization (GEO)?
Generative Engine Optimization is the practice of getting a brand named and cited inside answers that AI engines compose, rather than ranked as a link on a search results page.
The short version
When a buyer asks an AI engine for a shortlist, they get three names and a paragraph of reasoning instead of ten blue links. GEO is the work of being one of the three. The technical groundwork overlaps with classic SEO, but the main lever is different: what independent sources say about you matters more than what your own pages say.
The four layers, in order
Access - can crawlers physically retrieve your content. Entity - does the engine know who you are without contradictions. Shelves - do your pages contain passages worth quoting. Placements - do the sources the engine already trusts in your category mention you. The order matters, because building pages while your crawler is blocked is spending money on something nobody will read.
How it is measured
A fixed panel of buying prompts, run three times each because model answers are not deterministic, recorded before and after against the same engine. You track whether the brand was named, in what position, and which sources the answer cited. A single run of a single prompt is noise, and any before-and-after built on single runs should be ignored.
What does not work
llms.txt is currently placebo - Ahrefs found 97% of files across 137,000 domains received zero requests, and Google has said it will not use it. General schema markup shows no citation effect across published testing. Both are worth doing as cheap hygiene and neither belongs on an invoice as a growth deliverable.
Timeline reality
The lag between a third-party placement going live and it appearing in AI answers runs roughly four to eight weeks. Any engagement shorter than a quarter ends before the first genuine signal arrives, which is why serious programs are sold in quarters and dramatic three-week results should be treated as measurement error.
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