Guide · GEO
LLM SEO, explained by a team that does it.
Buyers now put their questions to ChatGPT and Perplexity before they put them to Google, and the model answers by naming a handful of sources. LLM SEO is the work of being in that handful. Here is what it means, what changes from the SEO you already do, and a method you can start this week.
This guide, in 6 parts
LLM SEO is ranking inside the answer.
For twenty years, search meant a list of links and the work meant climbing it. A growing share of buying research now starts as a question typed into ChatGPT or Perplexity instead, and what comes back is not a list. It is one short answer, assembled from a handful of sources the model chose to trust, with the names of those sources attached.
LLM SEO is the work of being one of those names: identified correctly, quoted accurately, and recommended when a model answers questions in your category. The label is young. GEO, AEO, AI SEO and LLM SEO all describe the same job, and we treat them as one discipline. We also practice what follows on this very site: we rank our own site and measure it.
« If the model does not name you, the buyer never learns you exist. »
What changes from classic SEO.
Most of your SEO foundation still counts. Crawlability, speed, clean structure and real authority decide whether you are in the pool a model retrieves from at all. What changes is what wins once you are in the pool, and it changes in four places.
The unit of competition is the passage
A model does not send the buyer to your page. It lifts a paragraph, blends it with others, and writes one answer. A paragraph that only makes sense after the three above it will never be lifted. Classic SEO ranked pages. LLM SEO wins passages.
Entities anchor the answer, keywords do not
Before a model recommends you, it has to resolve you to a single company: one canonical name, a plain-sentence About page, Organization and sameAs structured data pointing at your external profiles. Two trading names and three conflicting descriptions read as three different companies, and none of them gets cited.
Corroboration counts alongside backlinks
Backlinks pass authority. Models also cross-check facts: what your directory listings, press mentions, partner pages and review profiles say about you. When the rest of the web repeats your category, your location and your claims in the same words, the model can trust them. When it contradicts you, it hedges or skips you.
The prize is the citation, and the click may never come
Pew found that when an AI summary appears, only about 8% of Google visits end in a click on a result. The buyer reads the answer, remembers the names inside it, and often arrives later by typing yours directly. Winning now means being quoted, not just listed.
We wrote a companion guide on the citation mechanics themselves, with a before and after rewrite of a real paragraph: how to get cited by ChatGPT, Perplexity and AI Overviews.
The method, in five steps.
In order. Step one is the one most teams skip.
Write down the questions you have to win
List 20 to 50 questions your buyers actually ask, pulled from sales calls, support tickets and the questions Google shows under your keywords. Then ask each one in ChatGPT, Perplexity and Google, and record who gets named. This baseline is your prompt panel, and every later step is judged against it. Most companies skip this and start rewriting pages blind.
Make your company resolve to one entity
One canonical name, used identically everywhere. An About page that defines what you do, for whom and where, in sentences a model can lift. Organization and sameAs structured data linking your site to LinkedIn and the registries. If your own web presence disagrees with itself, no amount of content fixes it.
Reshape the pages that should answer
Turn headings into the buyer's question and answer it in the first two sentences underneath. Make paragraphs self-contained. Give each page one specific claim a competitor cannot copy: a number, a date, a named source. The peer reviewed GEO study measured up to 40% more visibility in AI answers from adding citations, quotations and statistics, while keyword stuffing performed poorly.
Earn corroboration off your own site
Get the same facts repeated where models look: industry directories, press, partner pages, review platforms, your founders' public profiles. This is slower than editing your own pages and it matters at least as much, because a claim only you make is a claim, and a claim three independent sources repeat is a fact the model can use.
Rerun the panel monthly and iterate
Ask the same questions, the same way, every month. Score how often you are named, cited or recommended per engine, watch which changes moved which answers, and put the next month's work where the gaps are. The loop is the method. A one-off audit decays in a quarter.
The tools question, answered honestly.
If you searched "llm seo tools", here is the map as it stands in 2026. Three categories exist, and they answer different questions.
Classic SEO suites with AI answer tracking. Semrush and Ahrefs now report whether AI Overviews appear on your keywords and whether you are cited inside them. If you already pay for one, turn those reports on before buying anything else.
Dedicated share-of-answer platforms. Tools like Profound query the engines at scale across prompt sets and report who gets named, per engine, over time. Built for teams that need daily sampling across many questions and markets.
A spreadsheet and an hour a month. Your own prompt panel, run by hand. Free, slow, and good enough to start. It is how we began on our own site.
We will not attach scores or prices to any of these. The category is young, features ship monthly, and a comparison table written today would mislead you by the time you read it. Pick by the question you need answered, not by the longest feature list. And keep the caution in view: a tool reports the score, while moving it is content, entity and corroboration work that no dashboard does for you.
Measure share of answer, not rank.
The number that matters is share of answer: across your fixed question set, how often each engine names, cites or recommends you, and how that moves month over month. We keep a full guide to the measurement itself, panels, tools and the free way to start, at AI search visibility: tools and how to measure it.
Watch the indirect signals too. Referrals from chatgpt.com and perplexity.ai in your analytics. Branded search volume drifting up while generic clicks drift down. A "how did you hear about us" field on your forms, because buyers who found you in an answer will tell you so. None of these is precise on its own. Together they tell you whether the answers are working.
This loop, audit, build, corroborate, measure, is what we run for clients as Be the Answer, our operator-led GEO program.
Frequently asked.
What is LLM SEO?
LLM SEO is the work of making your company visible, cited and recommended in the answers large language models give, in ChatGPT, Perplexity, Claude and Google AI Overviews. It covers three jobs: making your company easy to identify, making your pages easy to quote, and getting the rest of the web to corroborate what you say. The goal is to be named inside the answer, because the answer often replaces the click entirely.
Is LLM SEO the same thing as GEO or AEO?
In everyday use, yes. GEO (generative engine optimization), AEO (answer engine optimization), AI SEO and LLM SEO are competing labels for the same discipline, and the market has not picked a winner. The techniques underneath are identical. Pick a label and start the work.
Does classic SEO still matter?
Yes, and more than the hype admits. AI engines retrieve from an index before they write, so a site that is slow, thin or hard to crawl never enters the pool the model quotes from. Classic SEO gets you into the pool. LLM SEO decides whether the model picks you once you are there.
How do you measure LLM SEO?
Share of answer: across a fixed set of buyer questions, how often each engine names, cites or recommends you, tracked month over month. You can run it manually with a spreadsheet or pay a tracking platform to sample at scale. Rankings and sessions will understate your progress, because buyers increasingly read the answer without visiting anyone.
You can run much of this yourself. The panel, the entity fixes and the rewrites are all above, and a capable team can ship them. Bring us in when a competitor is being cited in your place, when organic traffic is eroding faster than you can rewrite, or when you want the loop run for you and measured. That work is Be the Answer.
Want to know what the models say about you?
No deck, no gate. A working session on your AI visibility, with the team that would do the work.