Generative engine optimisation, or GEO, is what you do to make AI assistants treat your content as a trusted source worth quoting. The shift it responds to is straightforward: people increasingly get answers from ChatGPT, Perplexity, and Gemini rather than from a page of links, so the prize is no longer a high ranking but a citation inside the answer itself. GEO competes for that citation. It keeps much of what good SEO taught, namely quality, authority, and sound technical foundations, but adds a new test, which is whether a model can find your content, trust it, and lift a clean answer out of it.
How GEO differs from SEO
SEO and GEO share foundations but optimise for different outcomes. SEO is built on links, keywords, and ranking position in a results page that the user then clicks through. GEO is built on language, entities, and the ability of a model to confidently extract and attribute your content inside a generated answer. In SEO, success is a high-ranking blue link. In GEO, success is your brand or content appearing in the answer itself, often without a click at all. The two are not opposites; well-structured, authoritative content tends to help both. But GEO adds requirements that classic SEO never had, because the consumer of your content is now a model assembling an answer, not only a person scanning links.
What makes content more likely to be cited
AI systems favour content they can trust and extract cleanly. The factors that repeatedly correlate with being cited include evidence-backed authority, where original research, verifiable statistics, and data get cited far more than unsupported opinion; clear structure, where descriptive headings, direct answers, tables, and schema markup make content easy for a model to parse and reuse; transparency and credibility, where clear authorship, citations, and data provenance let a model verify the source; and freshness, where recently updated content is cited substantially more often than stale content. Multi-platform presence helps too, because entity clarity across many sources makes a brand easier for a model to recognise and reference.
How to do GEO in practice
Start each important page with a direct, self-contained answer to the question it targets, placed near the top so a model can lift it. Use question-format headings that match how people actually ask. Support claims with specific figures and name your sources. Add structured data so machines can read the page's meaning, not just its words. Make your brand and product entities consistent and unambiguous wherever they appear. Keep the page current, and revisit it when facts change. Finally, build a presence across the different sources that different assistants rely on, since each one weights its citations differently.
How to measure GEO
GEO needs a different metric stack from SEO. Instead of rankings and organic clicks, track mention rate, how often your brand or content appears in answers to category questions; citation rate, whether models attribute specific claims to your content; share of voice, your mention frequency relative to competitors; and the sentiment and prominence of those mentions. Measure each assistant separately, because the same content can perform very differently across ChatGPT, Perplexity, and Gemini. A growing set of tools runs fixed prompt sets across assistants and reports where you appear.
GEO and the publisher monetisation question
For publishers, GEO and monetisation are two halves of the same shift. GEO determines whether AI systems cite your content. The separate, related question is whether you earn anything when they read it. Live Search Agents retrieve publisher pages to build answers, and that read generates no revenue through traditional means because the agent runs no JavaScript. GEO makes you the source AI reads; content-layer monetisation lets you earn from that read. blankspace operates on the monetisation side, intercepting Live Search Agent retrievals at the CDN edge and turning them into measurable revenue, and it provides the traffic and audience data that show which content AI systems are actually retrieving. Strong GEO increases the retrievals; monetisation captures their value.
Frequently asked questions
Is GEO the same as AEO or AI SEO?
The terms overlap. GEO, generative engine optimisation, and AEO, answer engine optimisation, both describe optimising to be cited in AI-generated answers. Some practitioners use them interchangeably and others draw fine distinctions. The shared goal is being the trusted source an AI quotes.
Does GEO replace SEO?
No. They coexist. SEO still drives traditional search visibility, and well-structured authoritative content helps both. GEO adds requirements for being extracted and cited by models, which matters more as AI answers replace clicks.
How do I know if my content is being cited by AI?
Run a fixed set of relevant questions across ChatGPT, Perplexity, and Gemini and record whether your content is named or quoted, or use an AI visibility tool that tracks citations and share of voice continuously across assistants.
What content gets cited most by AI?
Factual, well-structured, clearly sourced, and recently updated content with direct answers near the top. Original research and verifiable data are cited far more often than unsupported opinion.
How does GEO relate to earning revenue from AI traffic?
GEO determines whether AI systems retrieve and cite your content. Monetisation determines whether you earn when they read it. They are complementary: GEO increases AI retrievals, and content-layer monetisation turns those retrievals into revenue.