Generative Engine Optimization (GEO)

Classic SEO optimizes for a ranked list of links a human scans. GEO optimizes to be the cited source inside a single synthesized answer. The engine reads many pages, decides which few to trust, and names them. You are no longer competing for position three — you are competing to be quoted.

That changes what good content looks like. Hedge-y marketing prose is hard to quote. A plain sentence with a specific number, a clear definition, or a direct answer to a question is exactly what a model lifts.

I stopped guessing at this in August 2026 and pulled the data on my own site. The pattern in what won citations was duller than any framework I had read: the pages an engine named led with an explicit number or a price table in the first screen. The pages it retrieved and dropped, including mine, opened with context and worked up to the number several paragraphs later.

So the first rule is position, not prose quality. Put the specific — the load time, the price, the timeline, the count — in the opening block where a model composing an answer can lift it without reading around it. Everything else in this discipline is downstream of that habit.

Structure and trust still matter after that. Schema (Service, FAQPage, Place, DefinedTerm) tells an engine what it is reading, a named author with stated expertise and an organization entity whose details agree across every surface tell it whether to rely on you. Contradicting yourself is the cheapest way to lose a citation you had already earned.

The most practical GEO tactic is to write, on every important page, a short standalone block that answers the page’s core question with a specific — then back it with schema. That gives the engine a ready-made, attributable quote.

It also helps to control how AI crawlers see your site: explicitly allowing answer-engine bots, publishing an llms.txt, and emitting clean JSON-LD all reduce the friction between your content and a citation.

For a service business, most AI queries are local: “who’s a good tree service near Lowell?” The same dedicated town pages and LocalBusiness schema that win the Google map pack are what an AI engine reads to decide which local business to name. GEO and local SEO are two views of the same well-structured content.

In August 2026 I ran a DataForSEO LLM-mentions pull against builtwithdias.com to find out where I actually stood, rather than assuming. ChatGPT returned three prompts — whether local SEO is worth it, and two variants of what it costs. My pricing guide was retrieved for all three. It was cited in none. Reddit, BrightLocal, Search Engine Land and SEO.com took those citations instead.

That is worth sitting with, because it reframes the problem. I was not invisible to the engine; I was visible and passed over. Those are different failures with different fixes, and almost every article about ranking in AI search conflates them. If you have never measured which one you have, you are optimizing blind.

The demand picture changed underneath the terminology too. The head term “generative engine optimization” still draws about 4,400 US searches a month but has fallen roughly a third year over year and carries a difficulty of 54. Meanwhile “ai seo services” runs 1,000 a month at a difficulty of 2 with an average cost per click of $78.77. Buyers moved to the plainer words while the industry kept branding the acronym.