AEO / GEO explained

Answer engine optimization,
without the acronym soup.

AEO, GEO, AI SEO and LLM SEO all describe one shift: from ranking on a page to being the business an AI names. Here's what that actually requires, and how to measure whether it's working instead of guessing.

  • The terms, defined and disambiguated
  • What engines reward, in priority order
  • A measurement method, not just tactics
  • Free baseline check on your own domain

The terms, quickly

SEO optimizes for a ranked list of links. AEO (answer engine optimization) optimizes to be cited inside a synthesized answer. GEO, generative engine optimization, is the same idea under a different label. AI SEO and LLM SEO are umbrella terms covering both plus the AI-aware parts of classic SEO. The distinction worth keeping is not between the acronyms. It's between readiness and outcome: whether your site is structured to be citable, and whether engines are in fact citing you. They need separate measurement.

What answer engines reward, in order

1. Resolvable identity. Organization schema with a name, URL, logo, description and real sameAs profiles, present sitewide. An engine that can't tell which company you are will not risk naming you. 2. Cross-surface consistency. The same brand description, word for word, in your meta, OG tags, JSON-LD, footer and About page. Contradictions between surfaces get dropped, not reconciled. 3. Quotable specificity. Numbers, dates, named clients, stated opinions. Generic claims are unquotable because they're indistinguishable from every competitor's. 4. Trust signals. Named people, publish and update dates, outbound citations, reachable contact details, policy pages. 5. Distinctness. Location and product pages that share 80% of their text with each other are deduplicated, and the survivor may not be yours.

Why readiness alone isn't the metric

A site can score well on every structural check and still never be named, because a better-known competitor owns the query. That's the limitation of any audit-only tool: it grades the page, not the outcome. So start from the outcome. Ask the engines your buyers' questions, record who gets named, then use the structural audit to explain the gap on the specific pages you lost. Audit as diagnosis, not as scoreboard.

A practical starting sequence

Run a baseline visibility check on ten real buyer questions and save the result. Fix identity first: Organization schema, sameAs, one description reused verbatim. Then de-duplicate your templated pages. Then add dates, named humans and concrete numbers to the pages that matter commercially. Re-run the same ten questions monthly against the saved baseline. That loop is the whole discipline. Everything else is vocabulary.

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