LLM SEO: What It Is, What Actually Works, and What We've Tested on Our Own Site

TL;DR: LLM SEO is the practice of structuring your website, your content, and your off-site footprint so large language models can find your business, trust it, and recommend it in their answers. It is not a replacement for SEO. It is SEO extended to a second set of readers: the AI engines your customers now ask first. Below: the definition, how it relates to AEO and GEO, the tactics with real evidence behind them, and what happened when we ran this playbook on our own site.

What is LLM SEO?

LLM SEO (large language model search engine optimization) is the practice of optimizing your website and digital presence so AI systems like ChatGPT, Perplexity, Claude, and Google's AI Overviews can find your content, understand what your business is, and cite or recommend it in their generated answers. Traditional SEO earns you a ranking. LLM SEO earns you a mention in the answer itself.

That distinction matters because the answer is increasingly where the click used to be. When a customer asks ChatGPT "who should I hire for X near me," there is no page two. There are three to five names, and the model picked them before your homepage ever loaded.

Is LLM SEO the same thing as AEO or GEO?

Mostly, yes. LLM SEO, AEO (answer engine optimization), and GEO (generative engine optimization) are overlapping labels for the same shift, used with slightly different emphasis. AEO focuses on formatting content so answer engines can extract it cleanly. GEO focuses on brand presence across AI-generated summaries. LLM SEO is the umbrella: everything that makes language models find and trust you.

The industry has not settled on one name, and honestly, the label matters less than the work. Here is how we separate them when scoping projects:

	SEO	AEO	GEO / LLM SEO
Goal	Rank in search results	Be extracted as the direct answer	Be recommended across AI responses
Unit of success	A position	A cited passage	A brand mention
Main levers	Content, links, technical health	Question structure, concise answers, schema	Entity consistency, third-party corroboration, everything left of this column
Where it shows up	Google, Bing	AI Overviews, featured snippets, voice	ChatGPT, Perplexity, Claude, Gemini, Copilot

We wrote a deeper comparison in AEO vs. SEO if you want the full breakdown.

Does traditional SEO still matter for LLM visibility?

Yes, and more than most LLM SEO content admits. AI engines that search the live web (ChatGPT search, Perplexity, AI Overviews) pull from existing search indexes. If nothing about your business ranks anywhere, retrieval-based AI has nothing to retrieve. Crawlability, indexation, and ranking are the entry ticket. LLM SEO decides what happens after retrieval.

But here is the wrinkle we found measuring our own site: it is not just Google's index anymore. When we installed Microsoft Clarity's AI visibility tracking, our most-cited page in Copilot ranked #66 on Google. Copilot reads Bing's index. Different engines read different indexes, and a page invisible in one can be a workhorse in another. We call this the Two-Index Problem, and it changes where you spend effort: submitting to Bing via IndexNow stops being optional busywork and becomes a direct AI-visibility lever.

How do you actually do LLM SEO?

Six things, roughly in order of leverage. This is the same sequence we run for AI SEO clients.

1. Fix the entity before the content

An LLM deciding whether to recommend you first has to resolve what you are. Same business name, same category description, same location, same offerings, everywhere: your site, Google Business Profile, LinkedIn, directories, schema. Inconsistent entity data is why models confuse businesses with similarly named companies or file them under the wrong category. We learned this one publicly when ChatGPT called our AI company a marketing agency.

2. Answer first, elaborate second

Under every question-shaped heading, put a self-contained 30 to 60 word answer before the storytelling. AI extraction is lazy in the best sense: it clips the cleanest complete passage it can find. If your answer needs three surrounding paragraphs to make sense, the model takes someone else's. You will notice every section of this post does exactly this.

3. Give the model something worth quoting

The original GEO research out of Princeton and IIT Delhi tested which content changes made AI engines more likely to include a source, and the winners were adding quotations, statistics, and citations to credible sources, with visibility gains of roughly 30 to 40 percent in their benchmarks. Generic advice gets paraphrased without attribution. Specific numbers, named methods, and first-hand results get cited. This is why we publish our own receipts instead of borrowing stock statistics.

4. Structure for machines without writing for robots

Comparison tables, step lists, descriptive natural-language URLs, schema that matches what is visibly on the page. One caution: in a controlled test where AI chatbots fetched pages directly, they read only the visible rendered text and missed facts that existed solely in JSON-LD. Engines answering from a search index may still use schema, so keep it, but the safe rule stands: if a fact matters, say it in the visible copy too.

5. Get corroborated off your own site

Models weigh consensus. A claim that exists only on your domain is an assertion; the same claim echoed by directories, reviews, press, and forums is a fact. This is the least glamorous part of LLM SEO and the part most on-page checklists skip entirely. Reviews, local citations, and third-party mentions move AI answers in ways one more blog post cannot.

6. Keep it fresh

Retrieval engines favor recently updated sources, and we keep seeing fresh pages get admitted fast: a service page we shipped this week was crawled and indexed by Google overnight, and a research post reached page one within days of publishing. On a young domain, publishing consistently and updating what you have already ranked beats stockpiling new posts.

What about llms.txt?

llms.txt is a proposed standard: a plain-text file that hands AI crawlers a curated map of your site. The evidence on it is genuinely mixed. Google says its AI systems do not use it. Ahrefs checked 137,000 domains and found 97 percent of llms.txt files had never been fetched by an AI crawler, while CDN logs from documentation platforms show steady AI-tool requests for theirs. It takes minutes to ship and carries no penalty, so we include one as a hedge on every build. What we will not do is sell it as a flagship tactic, because the data does not support charging for it that way.

How do you measure LLM SEO?

Three signals, none of which show up in a classic rank tracker. First, direct probes: ask each engine the questions your customers ask and record who it names. Second, citation telemetry: Microsoft Clarity now reports which of your pages AI engines cite. Third, referral traffic from AI surfaces in your analytics. We run all three on our own domain, which is how we can tell you it works: when we asked four AI engines who to hire for AI search in Central Florida, three named us. In a separate check, Perplexity ranked us first for a local AEO query, and one of its stated reasons was a receipt page we had published five weeks earlier.

Common questions

Will AI replace SEO?

No. It is absorbing SEO. The engines generating answers still depend on crawlable, rankable, trustworthy web content, and Google has said outright that showing up in AI features runs on its core ranking systems. The skills transfer; the scoreboard changed.

What is LLM SEO called? LLMO? GEO? AEO?

All of those labels are in circulation, plus AI SEO and answer engine optimization. Pick any of them and practitioners will know what you mean. The work underneath is one discipline.

Is LLM SEO worth it for a small business?

It is often worth more for a small business than a big one. AI answers flatten the pack: the model recommends whoever is clearest, most consistent, and best corroborated, not whoever has the biggest domain. A well-structured local business can out-answer a national brand in its own service area. That asymmetry is the whole reason we built our AI SEO service around it.

Where do I start?

Run an audit before you touch anything: what do the engines say about you today, what does your entity footprint look like, what already ranks. Our free AI visibility audit does the first pass in about 30 seconds, and it is the same check we run before every engagement.