GEO (Generative Engine Optimization) explained

If you’ve been pitched AEO, GEO, AI SEO and LLMO as four different services, you’ve met the industry’s naming problem, not four different kinds of work. The terms differ in emphasis; the discipline underneath is one thing.

The terminology, untangled

The differences are of emphasis, not substance. AEO frames the outcome from the buyer’s side — the answer they hear. GEO frames it from the machine’s side — the engine’s mentions and the sources it cites. The work underneath — presence, consistency, third-party credibility, quotable content, honest measurement — is identical.

Why the term exists at all

GEO entered circulation through academic research on how generative engines select and cite sources — the 2023 paper that coined the term tested whether changes to content (citing sources, quoting authorities, including statistics) changed how visible that content was in generated answers, and found that they measurably did. The term stuck because it usefully covers more than commercial recommendations: citations in research-style answers, mentions in comparisons, presence in AI-generated overviews. If AEO asks “who gets recommended?”, GEO also asks “who gets cited along the way?”

GEO for publishers vs GEO for service businesses

The research framing fits publishers best: sites whose product is content, competing to be the cited source inside an answer. A local service business is playing a related but distinct game — competing to be the subject of the answer, the name recommended rather than the source quoted. Publishers optimize their prose; service businesses optimize their evidence trail. The tactics overlap (structure, clarity, authority) but the scoreboard differs, which is why a plumber copying a publisher’s GEO checklist wastes effort on the wrong half of it.

For a service business, the working definition is simple: GEO/AEO is everything that makes engines more likely to say your name, and measurement is how you know it’s working. The rest of this page is that version.

The starter playbook

• Baseline first: measure how often the engines name you today, across engines and repeated runs — one chat proves nothing.
• Read the citations in your category’s answers; they are the map of sources that matter.
• Claim, complete and reconcile every profile on that map — to a machine, consistency is credibility.
• Earn third-party words: reviews naming your service and city, local press, industry listings.
• Publish plain, quotable answers to real buyer questions, marked up with structured data.
• Re-measure monthly with the same questions, and manage against the frequency.

That list is deliberately identical to the ChatGPT playbook — same discipline, remember. The measurement protocol we use is public on the method page.

How to talk to vendors about GEO

Whatever a proposal calls itself — GEO, AEO, AI SEO — four questions expose whether there’s a real practice behind it. How many times do you run each prompt? (One-run screenshots aren’t measurement.) Which engines do you cover, and are they reported separately? Can I see the raw answers my numbers came from? And what specific work happens in the first month — which sources, which fixes, in what order? A serious vendor answers all four without flinching; ours are public on the method page.

See where you actually stand across six engines on the leaderboard, or get your own count with a free scan. Whatever name the industry settles on, the number is what matters — counted, not claimed.