SEO explained
LLM SEO: getting cited in AI answers
LLM SEO is the practice of making your content easy for large language models to read, trust and quote, so your brand appears inside AI-generated answers rather than only in a list of links. It goes by three other names — generative engine optimization (GEO), answer engine optimization (AEO) and LLM optimization (LLMO) — and they describe the same work.
Why it is not a separate discipline
Every credible account of this ends up in the same place: the inputs are the ones SEO already cares about. Assistants are grounded on pages they can crawl, and they lean on sources that are structured, specific and corroborated elsewhere. A site that is crawlable, factually clear and cited by others is the site that gets quoted.
What changes is the unit of success. Ranking asks which page sits at position three; citation asks whether your name appears in a sentence someone reads instead of the results page. You can hold position one and be absent from the answer above it, which is the whole reason this has its own vocabulary.
The four names, and whether the difference matters
GEO — generative engine optimization — is the term academic work and most tool vendors use. AEO — answer engine optimization — comes from the voice-assistant era and stretches to cover featured snippets and People Also Ask as well. LLMO, LLM optimization, is the newest and the most ambiguous, because engineers use the same phrase for making models run faster.
In practice they are interchangeable and nobody will misunderstand you whichever you pick. Treat a vendor who insists their acronym is a distinct discipline with the scepticism that claim deserves.
What plausibly moves citation
Answer the question in the first sentence, in plain words, near the top. Extraction favours a self-contained claim over a paragraph that builds to a point — which is also what wins a featured snippet, so this is not a new investment.
Be specific enough to be quotable. Numbers, dates, named entities and stated limits give a model something to lift; hedged prose gives it nothing. And be corroborated: models weight claims that agree with other sources, so being the only page saying something is a disadvantage here even when it is true.
Then let crawlers in. If your robots.txt blocks GPTBot, ClaudeBot and the rest, none of the above applies to you — which is a legitimate choice, just an explicit one.
How to tell whether it is working
Rankings will not tell you. The measurement is whether your brand is named for the prompts your buyers actually type, which means asking the assistants and recording the answers over time — the same way rank tracking works, with prompts in place of keywords.
Watch two things separately: whether you are mentioned at all, and whether the page you wanted is the one cited. Being named while a competitor's comparison page is the citation is a different problem from not being named.
Questions people ask
- Is LLM SEO the same as GEO and AEO?
- Yes. Generative engine optimization, answer engine optimization and LLM optimization all describe optimising to appear inside AI-generated answers. The labels come from different vendors and moments, not from different methods.
- Do I need to stop doing normal SEO?
- No, and that would be the expensive mistake. Assistants are grounded on crawlable pages and favour sources cited elsewhere, so technical health and links still do the work. This is an additional way of measuring the same effort.
- Does llms.txt help me get cited?
- There is no evidence yet that it does. It is a proposed convention, not something the major assistants have committed to reading, so treat it as cheap and speculative rather than as a lever.
Tools that answer this on your own site
- Brand Lookup
How often models mention and cite your brand
- Prompt Explorer
One prompt, four models, answers side by side
Read the theory, then check your own site
The free plan opens every tool with 500 credits and no card, so you can look at your own numbers rather than an example.
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