Answer engine optimization (AEO)

Classic search returns a list, and the same query returns roughly the same list to everyone. An answer engine composes a response, and two runs of the same prompt minutes apart can name different businesses. That single difference breaks most of the measurement habits SEO taught us.

The most important consequence: there is no stable position to report. A brand is not ranked third in an AI answer. It is either present in a given answer or it is not, and the honest measurement is the share of sampled answers where it appeared, with the sample size attached.

Two things have to be true. The engines have to be able to fetch and parse your pages, which is a retrievability problem. And the sources those engines already cite for your category have to mention you, which is an earned-mention problem.

The second is usually the binding constraint. Engines answering commercial questions lean heavily on third-party sources: review sites, forum threads, roundups and comparison pages. A brand can have a perfect website and still be absent from every answer because it is absent from every source the answer was built from.

Treating AEO as a checklist of on-page markup. Structured data helps machines parse your facts without guessing, which is worth doing, but we have seen no measured evidence that adding schema causes an engine to cite you. We say so on our methodology page, and our free schema generator says it on the tin.