Generative engine optimization
Generative engine optimization (GEO)
GEO is the work of improving how your brand appears inside AI-generated answers — named, cited, and recommended in generated output rather than ranked in a list of links.
GEO, AEO, AI visibility: what the words are doing
| Term | Usually means | Mostly used by |
|---|---|---|
| GEO | The work of improving presence in AI-generated output | Agencies and consultants selling the work |
| AEO | The same work, framed around being the answer to a question | Agencies and consultants selling the work |
| AI visibility | The measurable state — are you named, cited, recommended | Tools measuring it |
| AI search monitoring | Measuring that state repeatedly over time | Tools measuring it |
The distinctions are soft and the usage is inconsistent across the industry. We would rather say that than pretend there is a settled taxonomy we happen to own.
What generalises, and what does not
GEO advice circulates as universal rules. Most of it is inference from small samples, including ours. What we can say from our own measurements, on our own categories:
- Engines disagree with each other constantly. The same question produces different named brands on ChatGPT, Gemini and Perplexity often enough that a single-engine result should never be generalised to "AI".
- Recommendation is steadier than the competitor set. Across repeated runs, whether a brand was recommended held; the exact list of other brands named moved. Treat competitor share as directional.
- Citation and recommendation are not the same lever. A brand can be cited as a source and still not be recommended, and the reverse happens too. They need separate measurement and separate work.
Those are observations from our data, not laws. Anyone stating GEO rules as settled science — us included — should be asked what they measured and how many times.
How to tell whether GEO work is doing anything
The same standard as any other channel: a frozen question set, a stored baseline, per-engine reporting, failures excluded from denominators, enough runs to be comparing states rather than samples, and an explicit acknowledgement that a change you measured is not proof you caused it. See AI search monitoring.
Common questions
What is generative engine optimization (GEO)?
GEO is the work of improving how a brand appears inside output generated by AI systems — being named, cited and recommended in generated answers rather than ranked in a list of links.
Is GEO the same as AEO?
The terms overlap almost entirely in practice. GEO is usually framed around generated output broadly, AEO around being the answer to a question. Neither has a standards-body definition.
Does GEO replace SEO?
No. Much of what makes a page citable by an AI assistant is the same work that makes it findable: it exists, it is crawlable, it answers the question, and other credible sources reference it. What changes is the outcome you measure.
What we actually measure
Every result comes from the official OpenAI, Google Gemini
and Perplexity APIs with web search or grounding enabled. In our data those
surfaces are recorded as openai_api_web_search,
gemini_api_google_search and perplexity_api_sonar, and reports name
them explicitly.
That is not the same thing as a logged-in person using the ChatGPT app. These are official interfaces with web search on, but they are measurement surfaces rather than consumer sessions: no personalisation, no memory, no app-only features. Results can differ from what any individual user sees, and we do not claim the two are identical. We would rather put that on the pricing page than in the small print.
Answer engine optimization (AEO) · AI visibility · Tools in this category
Founding pilot pricing while we validate. 14-day pilot, founder-run, cancel any time.