Generative engine optimization (GEO)
Generative engine optimization is the practice of increasing the chance that AI systems which write answers — ChatGPT, Perplexity, Google’s AI results, Copilot — draw on your content and name you as a source. There is no ranking position to win, only inclusion in a generated response.
Why it is a different problem
A search engine returns a ranked list of documents. A generative engine retrieves several sources, synthesises them into prose and cites some of them. There is no position two, the answer is different for every phrasing of the question, and it is different again tomorrow. You are not competing for a slot; you are trying to be the material the model finds most usable.
Two paths get you in. Either the assistant retrieves your page at question time — essentially retrieval-augmented generation over a search index, which means classic discoverability still governs everything — or your organisation is described often enough across the web that the model has absorbed it during training. The second path is slower, is not something you control directly, and is mostly a consequence of other people writing about you.
What appears to help
The evidence base here is thinner than the confidence of most articles about it, so treat these as reasoned practice rather than established fact:
- Self-contained, quotable passages. The same requirement as answer engine optimization: a paragraph that means something when lifted out.
- Specific, checkable claims. Concrete numbers, named limits and clear comparisons survive synthesis; adjectives get discarded.
- Off-site presence. Being described in comparisons, forum threads, documentation and reviews matters more than for classic SEO, because retrieval frequently surfaces third-party pages about you rather than your own.
- Consistent entity description. If you describe yourself the same way everywhere, the model has one coherent thing to say about you.
- Structural clarity. Semantic HTML, schema markup and honest headings make extraction easier.
What to watch out for
You cannot rank in an LLM, and anyone selling you a GEO position is selling something that does not exist. There are no keywords to target, no index to inspect, and no stable ordering. Output varies between users and sessions, so a single flattering screenshot proves nothing.
The distinction from AEO is also mostly marketing. Both terms describe writing clearly, structuring properly and being genuinely worth citing; treat them as one activity. And the uncomfortable part: the strongest single lever is still being a source worth quoting, which no amount of formatting substitutes for. Content that says something a model cannot get from ten other pages is what gets picked up.
Frequently asked questions
How do I measure whether GEO is working?
Imperfectly. The practical method is to keep a list of questions your customers actually ask, run them through the major assistants on a schedule, and record whether you are mentioned and whether the description is accurate. Referral traffic from assistants is a weak secondary signal, since most citations produce no click at all.
What is the difference between AEO and GEO?
Very little in practice. AEO emphasises being the extracted answer to a direct question; GEO emphasises being a source a generative system draws on when composing prose. The techniques overlap almost entirely, and no consistent industry definition separates them. Treating them as two budgets or two teams is a mistake.
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