What Is Generative Engine Optimization?
Generative engine optimization is the practice of improving how generative search systems understand, evaluate and reference your brand. It is young, it is evolving, and much of it rests on fundamentals you may already have.
A working definition
Generative engine optimization (GEO) is the practice of improving how generative search systems understand, evaluate and reference a brand and its content. The term was popularised by a 2023 academic paper that tested how content changes affected visibility in generative search responses, and it is now used broadly for work aimed at AI-generated answers.
It is a young field. Platforms change how they retrieve and cite sources, and much of what is published about GEO is opinion rather than evidence. A sensible approach treats it as an extension of good SEO and content practice, measured carefully, rather than a set of tricks.
How generative search chooses sources
Most generative search experiences work in two stages. First they retrieve: they search an index, their own or a partner’s, for pages relevant to the prompt. Then they synthesise: a language model reads the retrieved material and writes an answer, often citing some of the sources it used.
Your content needs to succeed at both stages. It has to be retrievable, which depends on crawl access, indexing and relevance, much like SEO. And it has to be useful to the model writing the answer, which favours clear statements, specific facts and credible sourcing. The details differ between platforms, and none of them publishes a complete account of how sources are chosen.
What tends to help
The evidence so far points to familiar qualities, applied with more discipline.
- Clear entity information: consistent company, product and people details across your site and the wider web
- Specific, verifiable content: numbers, dates, examples and named sources rather than general claims
- Original material: first-party data, research and expert commentary others can’t replicate
- Coverage of the surrounding questions buyers ask, not just your product pages
- Third-party presence: accurate coverage in the publications, directories and reviews cited in your category
- Accessible pages: important content in the HTML, fast to load, not hidden behind scripts or logins
What to avoid
Some tactics promoted as GEO are ineffective or harmful. Hidden text and instructions aimed at AI models are a form of manipulation that platforms actively work against. Mass-producing near-duplicate articles to “cover” every prompt tends to dilute a site rather than strengthen it. Files or markup created only for AI crawlers are not a substitute for accessible, well-structured pages, and there is limited evidence that major platforms rely on them.
It is also worth being wary of anyone who guarantees citations in a specific AI tool. No one outside those companies controls what their systems cite.
How to start
Begin by measuring. Build a prompt set from real buyer questions, test it across the platforms your audience uses, and record how often you are mentioned, how you are described and which sources are cited. That baseline shows whether your gaps are technical, content-related or about your wider reputation.
From there the work usually combines technical fixes, clearer and more evidence-rich content, consistent entity information, and efforts to earn coverage on the sources that matter in your category. Re-measure on a fixed cadence to see what is changing.
Key takeaways
- GEO is about being understood and referenced by generative search systems.
- It builds on SEO: content has to be retrievable before it can be cited.
- Specific evidence, original material and consistent entity data tend to help.
- Avoid manipulation tactics, and treat citation guarantees with suspicion.