GEO vs AEO vs SEO
GEO, AEO and SEO are three overlapping disciplines for getting found. SEO (Search Engine Optimisation) earns a position in a list of links. AEO (Answer Engine Optimisation) earns a direct answer in a featured snippet or voice result. GEO (Generative Engine Optimisation) earns a citation inside an AI-generated answer. They share foundations but optimise for different outputs.
- →SEO optimises for a rank in a list of links. AEO optimises for a single direct answer. GEO optimises for a citation inside a generated AI answer.
- →They overlap heavily: crawlability, structure and schema help all three at once.
- →Rubric focuses on the GEO and AEO layer, estimating how citable each page is to the six AI engines.
What is SEO?
SEO, Search Engine Optimisation, is the practice of earning higher positions in a traditional search engine's list of results. It optimises for ranking, and its levers are relevance (matching the query), authority (links and reputation) and technical health (crawlability, speed, indexing). The output SEO wins is a link the user clicks. SEO is the foundation the other two build on, because a page that cannot be crawled or indexed cannot win an answer box or a citation either.
What is AEO?
AEO, Answer Engine Optimisation, is the practice of structuring a page so it wins a single direct answer, such as a Google featured snippet, a voice assistant reply, or a "People also ask" entry. It optimises for the one best answer to a specific question, usually lifted from a single page. Its levers are a concise, self-contained answer near the top, question-shaped headings, and FAQ or HowTo schema. The output AEO wins is the answer itself, shown above or instead of the list.
What is GEO?
GEO, Generative Engine Optimisation, is the practice of making a page citable by generative AI engines such as ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot and Claude. It optimises for being quoted and named as a source inside an answer the engine writes by synthesising several pages. Its levers are everything AEO uses, plus clear entity signals so the engine knows who you are, sourced evidence so it trusts you, and render parity so no-JS crawlers can read you. The output GEO wins is a named citation in the generated text.
GEO vs AEO vs SEO compared
The three disciplines share a foundation but aim at different outputs. The table below sets them side by side.
| SEO | AEO | GEO | |
|---|---|---|---|
| Full name | Search Engine Optimisation | Answer Engine Optimisation | Generative Engine Optimisation |
| Target output | A rank in a list of links | One direct answer (snippet, voice) | A citation inside a generated answer |
| Query it wins | "best crm for startups" | "what is the best crm for startups" | "compare the best CRMs for a 10-person startup" |
| Key techniques | Relevance, links, technical health | Concise answer, FAQ/HowTo schema | Entity clarity, sourced evidence, render parity |
| How you measure it | Rank and clicks | Snippet ownership | Citations, with citability as an estimate |
| Primary surfaces | Results pages | Featured snippets, voice | The six AI engines |
How much do they overlap?
They overlap heavily, which is why you rarely optimise for one alone. A page that is crawlable, fast, well-structured, marked up with valid schema and backed by sources tends to rank, win answer boxes and get cited by AI at the same time. The differences are at the margin: SEO leans on off-page authority and links, AEO leans on a single tight answer, and GEO adds entity clarity and evidence so an engine will name you when it writes an answer from many sources. See what-is-ai-citability for why the GEO layer now needs its own attention.
Where Rubric fits
Rubric fits at the GEO and AEO layer. It estimates how citable each page is to the six scored AI engines, using 44 checks across the Known, Findable and Trusted pillars, and assumes the SEO basics are in place. It rewards a clean answer near the top (AEO), plus the entity signals and sourced evidence that get you named in a generated answer (GEO). To make your pages easier for engines to understand, start with schema-markup-for-ai-search, and read the-three-pillars for how the score is built.