# What is LLM SEO? How it works and what to do first (2026)

> LLM SEO gets your brand named and cited by ChatGPT, Gemini, Perplexity and AI Overviews. What it is, how AI picks sources, and our own ChatGPT test data.

Canonical: https://www.searchmaxxed.com/research/what-is-llm-seo
Last updated: 2026-10-27

EXPLAINER

LLM SEO gets your brand named and cited by ChatGPT, Gemini, Perplexity and AI Overviews. What it is, how AI picks sources, and our own ChatGPT test data.

BH

Brenden House

Founder of Searchmaxxed. We build agentic SEO and GEO workflows that help businesses rank on Google and get named in ChatGPT, then turn that search into more customers and revenue.

PUBLISHED 27 OCTOBER 2026 UPDATED 27 OCTOBER 2026 15 MIN READ

LLM SEO (large language model SEO, or LLM optimisation) gets your brand found, quoted and recommended by ChatGPT, Gemini, Perplexity, Claude and Google's AI Overviews. It's SEO with three extra jobs. Let AI crawlers in, write pages a model can lift an answer from, and get trusted outside sources to agree about you.

I'm Brenden House, and I run Searchmaxxed, an SEO and AI SEO agency for enterprise, B2B SaaS, venture-backed, manufacturing and public-sector companies. Here's what LLM SEO means, how models pick sources, and what we've measured ourselves.

## In summary

LLM SEO is SEO for answers: the aim is to be the company an AI tool names when your buyer asks it for a shortlist.

- Google says AI Overviews and AI Mode have no extra technical requirements. A page has to be indexed and able to show a snippet, so classic SEO still does most of the work.
- ChatGPT search finds pages through a crawler called OAI-SearchBot, and OpenAI says a site that blocks it won't appear in ChatGPT search answers.
- We tested 900 ChatGPT answers ourselves. About three in four results it reads never make the answer, so being chosen is the real job.
- AI answers lean hard on a few outside pages, such as lists and review directories, so mentions there count as much as your own site.
- Measure named answers and real enquiries. Treat any "AI traffic" spike in GA4 as a suspect until someone checks it for bots.

## What does LLM SEO mean?

LLM SEO means optimising your website and wider web presence so AI models can find your content, understand it and repeat it. A large language model (LLM) is the AI system behind ChatGPT, Gemini and Claude. It learns from huge amounts of text.

Too many names, one job.

| Term | What it means in plain words |
| --- | --- |
| LLM SEO | Getting named and cited by AI tools built on large language models |
| LLM optimisation (LLMO), or large language model optimisation | The same thing, without the word SEO; US sites spell it LLM optimization |
| GEO (generative engine optimisation) | Getting your business named in AI-written answers |
| AEO (answer engine optimisation) | Shaping pages so an engine can lift a direct answer, including Google's AI Overviews |
| AI SEO or AI search optimisation | The umbrella term for all of the above, alongside normal Google rankings |

Two more terms come up in every LLM SEO conversation. A citation is a link or source an AI answer shows beside its text, and a mention is your brand named in the answer.

At Searchmaxxed we use all of these words, because marketing teams search all of them. Underneath sits one job. That's why our [AI search optimisation service](https://www.searchmaxxed.com/services/ai-search-optimization) runs LLM SEO, GEO and AEO alongside technical SEO, with one team doing all of it. If you want the finer line between the labels, [GEO vs SEO](https://www.searchmaxxed.com/research/geo-vs-seo) sets it out.

## How do large language models find and choose sources?

Large language models learn about your company in two ways. One is the text they trained on, and the other is the live web searches they run while they write an answer. You can influence the live route this month. The training route moves slowly, since it reflects what the web said about you before the model's cut-off, and changes only with the next model.

| Route | How it works | What you control |
| --- | --- | --- |
| Training data | The model learned from a large snapshot of the web before its cut-off date | What other sites say about you, over years |
| Live retrieval | The tool searches the web, reads pages and cites some of them | Crawler access, page content, outside sources, this quarter |

Most LLM SEO effort pays off on the live route. Google describes the mechanism plainly. Its [guide to AI features](https://developers.google.com/search/docs/appearance/ai-features) says AI Overviews and AI Mode "may use a 'query fan-out' technique". That means "issuing multiple related searches across subtopics and data sources" to build one response.

Query fan-out is the AI tool splitting one question into several smaller searches. Your buyer types one question. The model then goes looking for five or six separate things, such as your category, your competitors, prices, reviews and integrations.

ChatGPT search runs its own searches too, so we tested how picky it is about the sources it cites. We put 300 Australian agency-buyer questions to ChatGPT three times each, with search on. It pulled 17,870 search results into those 900 answers and kept 4,389 as sources. Being found is the easy part. About three in four results it reads never make the answer.

That ratio is the whole case. Ranking gets you read. Your page's content, and what other sites say about you, decide whether you come out the other side as a citation.

## How is LLM SEO different from traditional SEO?

LLM SEO builds on traditional SEO rather than replacing it. The goal changes. SEO wins a ranked link a person clicks, while LLM SEO wins a sentence inside an answer, often with no click at all.

Google is clear about the overlap. Its AI features guide says a supporting link must be "indexed and eligible to be shown in Google Search with a snippet". Then it adds: "There are no additional technical requirements."

|  | Traditional SEO | LLM SEO |
| --- | --- | --- |
| What you win | A position in the ten blue links | A mention or citation in an AI answer |
| Who reads your page first | A person scanning results | A model reading many pages at once |
| Unit of competition | One keyword, one page | One buyer question, split into several searches |
| What counts off your site | Backlinks | Backlinks plus mentions on lists, review sites and press the model trusts |
| How you track it | Rankings, clicks, Search Console | Named answers per engine, citations, then enquiries |
| Crawlers that matter | Googlebot, Bingbot | Those, plus AI crawlers such as OAI-SearchBot |

The table hides one trap. People hear "new channel" and assume it's easier to win. Our keyword data says otherwise.

"GEO is a blue ocean" is wrong. In our 13 October keyword capture, Australian AI-topic keywords had a median difficulty of 55, against 29 for everything else, and 82% already showed an AI Overview.

So LLM SEO is no shortcut. The companies the models name tend to be the ones Google already trusts, plus something extra: clear answers and outside sources that back them up. Our full method for ChatGPT specifically sits in [how to rank in ChatGPT](https://www.searchmaxxed.com/research/how-to-rank-in-chatgpt).

## What does LLM SEO involve on a company website?

LLM SEO involves five jobs. Open the doors to AI crawlers, publish pages that answer whole buyer questions, and keep one consistent set of facts. Then earn mentions on the outside pages models trust, and measure what the answers say. Each is ordinary SEO work pointed at a new reader.

Here's the checklist I'd run on any enterprise or SaaS site before spending a dollar on anything fancier.

1. **Check crawler access.**  Read your robots.txt, then your CDN and firewall bot rules, since IT can block AI crawlers without marketing ever hearing about it.
2. **Check rendering.**  If your key copy only appears after JavaScript runs, test what a crawler receives and fix it with server-side rendering where it matters.
3. **Build answer pages.**  One page per buying question: category, use case, industry, integration, comparison, alternatives and pricing. Answer in the first two lines.
4. **Fix your facts.**  Product names, company name, leadership, locations, certifications and integrations should read the same on every page and in your structured data.
5. **Add schema that matches the copy.**  Organization, Product or SoftwareApplication, FAQPage and Article markup, stating the same facts the visible page states.
6. **Earn outside sources.**  Find the lists, review sites, publications and community threads the AI tools already cite for your category. Then earn a place on them.
7. **Track answers and enquiries.**  Ask the same buyer questions in each AI tool on a set schedule, then tie the visits back to pipeline in GA4 and your CRM.

### Who controls AI crawler access on an enterprise site?

Usually IT or security owns it, through robots.txt and the bot rules on your CDN or web firewall, and marketing rarely touches either. So we check it first.

OpenAI's [crawler documentation](https://platform.openai.com/docs/bots) gives you a choice that matters to legal and public-sector teams. It says "a webmaster can allow OAI-SearchBot in order to appear in search results while disallowing GPTBot". GPTBot collects content for model training, so you can stay out of training and still show up in ChatGPT search. Block the search crawler and you vanish. OpenAI warns: "Sites that are opted out of OAI-SearchBot will not be shown in ChatGPT search answers".

After a robots.txt change, OpenAI says it "can take ~24 hours" for its search systems to adjust. It's the fastest fix in LLM SEO.

### What do outside sources have to do with it?

A lot. AI answers draw from a short list of outside pages, and getting onto that list often matters more than another page on your own site.

Across 900 ChatGPT answers about Australian agencies, a single third-party "best agencies" site was cited in 168 of them. The next three were a second listicle, Semrush's agency directory and Clutch. If you want to be recommended, the job is getting onto the handful of pages the model already trusts.

The engines also disagree about which outside pages they trust. Perplexity cited a review directory (Semrush Agencies, Clutch, DesignRush and the like) in 36 of 44 agency answers. ChatGPT did it in 20 and Claude in 15. One agency's Clutch profile had six reviews and was cited 20 times.

Our panels covered agency questions, so your category's source list will look different. The pattern carries over, though. So find the handful of pages each engine leans on for your buyers' questions before you plan links, PR or other off-site work.

### A worked example: a SaaS company asks why ChatGPT skips it

Take a made-up company: a venture-backed procurement software firm that sells to mid-sized manufacturers in Australia and the US, and wants more pipeline. Its head of growth asks ChatGPT, "What's the best procurement software for a mid-sized manufacturer?" ChatGPT names three competitors. Theirs is missing.

Query fan-out explains most of the gap. To answer, the model searches for things like procurement software for manufacturers, competitor comparisons, pricing, ERP integrations and reviews, one after another. The company ranks for its brand name and a few blog posts. It has no manufacturing page, no comparison pages, no integration pages and nothing that explains how its pricing works. Four searches find nothing of theirs.

The fix list writes itself, row by row, from the searches the model runs:

| Search the model runs | What the company had | What it needs |
| --- | --- | --- |
| Procurement software for manufacturers | A general features page | An industry page for manufacturers, answer first |
| Competitor A vs competitor B | Nothing | Comparison and alternatives pages, fair and specific |
| Works with our ERP | A logo strip | One page per integration, saying what syncs and how |
| Pricing | Nothing on how pricing works | A plain answer on how pricing works, even without numbers |
| Reviews | A few old reviews on one site | Fresh reviews where the engines already look |

None of that is exotic. It's SEO pages built for the questions the model asks on the buyer's behalf. This is the work our Growth System and Agentic Search Engineering packages ship every month, counted as page releases you can check.

## Does llms.txt help LLM SEO?

An llms.txt file can help AI agents read your documentation, but it isn't required to appear in AI answers. Google's AI features guide doesn't mention it.

llms.txt is a proposed markdown file at your site root that summarises your key pages for AI tools. The [proposal itself](https://llmstxt.org/) says "thousands of sites publish an llms.txt file", and notes that OpenAI, Anthropic and Gemini publish one for their developer docs.

My view: it's cheap, so add one if you run a developer platform or large documentation set, where agents read your docs to write code. On a marketing site it ranks low. Crawler access, answer pages and the outside sources models cite all matter more.

## How do you measure LLM SEO?

Measure LLM SEO in three layers. Do the AI answers name you, do Google and AI tools send real visits, and do those visits become pipeline? Each layer has its own trap.

| Layer | What to track | Where |
| --- | --- | --- |
| Answers | A fixed set of buyer questions, run on a schedule in ChatGPT, Gemini, Perplexity, Claude and AI Overviews; which brands they name and which pages they cite | A visibility tool or a tracked panel |
| Visits | Google search clicks, including AI Overviews and AI Mode; referrals from AI tools | Search Console and GA4 |
| Pipeline | Demo requests, enquiries and deals from those visits | GA4 key events and your CRM |

Google's guide says traffic from AI Overviews and AI Mode sits inside Search Console's Performance report, in the "Web" search type. Since 31 August 2026, Search Console's Generative AI performance report also shows those AI impressions on their own, by page.

GA4 is where the worst errors hide. Here's what we found on an enterprise B2B client's account. A client's GA4 showed AI-assistant visits jump from 354 to 6,050 in a month. Almost none of it was real. About 5,700 came in three one-hour bursts: same 1920x1080 desktop Chrome, all new users, no referrer, about 20 seconds each, landing on two pages. Real AI traffic was 385 sessions against 354 the month before, roughly flat.

Then a quieter problem. A client's four enquiry types never counted as conversions. Their event names ran 41 to 50 characters; GA4 cuts at 40. The 40-character "career" event counted every time. Nobody had noticed, because the events still showed up.

Put those two side by side and a monthly report could show AI traffic up seventeenfold while enquiries sat at zero. Both numbers would be wrong. So check the tracking before you judge any LLM SEO result, because a dashboard can be wrong in both directions at once. If you want to run the answer layer yourself, our guide to [AI visibility tools](https://www.searchmaxxed.com/research/ai-visibility-tools) compares the software.

AI answers also change from one run to the next, so judge a quarter of results and never one screenshot on one day.

## Is LLM SEO worth it for B2B and enterprise companies?

LLM SEO is worth it when your buyers research with AI tools before they talk to sales, and when one won deal covers the work. In my view, both hold for most B2B SaaS, manufacturing and enterprise companies.

Many B2B buyers now ask AI tools for shortlists, comparisons and "does X work with Y" answers. If the model builds the shortlist without you, your sales team never hears about the deal, and nobody can tell you why it went quiet. That's harder to see than a lost ranking, because nothing shows up in your analytics.

It's less urgent in two cases. One is a company that sells mostly through tenders or existing relationships, where the buyer rarely searches. The other is a site with basic SEO problems: fix indexing and core pages first, because the models read what Google can read.

## Should you do LLM SEO in-house, with a tool or with an agency?

Do it in-house if you have SEO, content and web development people who can ship changes each week. Use a tool to watch the answers. Hire an agency when the plan keeps stalling between marketing, IT and the content queue.

| Option | Good for | Watch out for |
| --- | --- | --- |
| In-house team | Companies with SEO, content and developers on staff | Crawler and firewall changes stuck with IT |
| Visibility tool | Tracking named answers across engines | It reports the gap; someone still has to build the fix |
| Agency | Teams that need pages, technical fixes and outside sources shipped together | Retainers that sell reports with no changes to the site |

Whoever does it, ask for output you can count: pages shipped, fixes made, outside mentions earned, and named answers tracked against competitors.

## Where does Searchmaxxed fit?

Searchmaxxed is an SEO and AI SEO agency that does LLM SEO, GEO, AEO and technical SEO as one job. We work with marketing and growth teams at enterprise, B2B SaaS, venture-backed, manufacturing and public-sector companies. The aim: rank in Google and get named in ChatGPT, Gemini, Perplexity and Google's AI answers for the questions that bring pipeline.

Our packages differ in volume: page releases each month, and how much work we do off your site. A page release is an approved new page or a substantial rebuild of one.

| Package | Who it suits | What it includes |
| --- | --- | --- |
| Growth System | A company growing in one or two markets | 30 page releases a month, work on up to 4 existing pages, one qualified link action a month, AI visibility tracking |
| Agentic Search Engineering | A competitive category or several markets | 50 page releases a month, comparison, industry and integration pages, digital PR and link campaigns, AI answer tracking across ChatGPT, Gemini, Perplexity and AI Overviews |
| Custom & Enterprise | Several brands, several markets or a large site | Multiple markets, dedicated engineering, custom reporting and original first-party research |

Every managed package includes ongoing audits, a 90-day plan in weekly releases, the build work itself and a monthly decision memo. You own the site, repository, content and data from day one. If you'd rather start with a diagnosis, the AI SEO Audit takes five business days and shows where buyers search without finding you.

Here's how we do it. We build on a website you own, our Agentic Website. AI agents pull your Search Console and GA4 data, read the Google results and check what AI answers say about you and your rivals. That feeds the Managed Search Loop, which shows which page, fix or link should bring in the most enquiries next. We build it, check the live page and measure what changed. Off your site, the Off-Page Source Layer builds the links, digital PR and mentions the AI answers draw on.

Searchmaxxed's work has generated more than A$10 million in revenue through search for its clients.

## Is Searchmaxxed right for you?

Searchmaxxed suits marketing and growth leaders who want LLM SEO built and shipped, with Google and the AI answers handled by one team. It doesn't suit a team that only wants a dashboard.

| Searchmaxxed is a good fit if | Look elsewhere if |
| --- | --- |
| You want pages, fixes and outside sources shipped every month | You only want to watch your AI mentions; a visibility tool costs less |
| You sell B2B, SaaS, industrial or public-sector services where AI shortlists shape the deal | You sell mainly through tenders and relationships, with little research before contact |
| You compete in a crowded category or several markets | You want one schema fix or one page, not ongoing work |
| You want to own your site, repository, content and data | You can't give us a way to ship changes to your site |
| You want direct access to the people doing the work, with no account managers | You need search to fill this month's pipeline on its own |

If you're in the right-hand column, a tool or a small project will serve you better.

## Frequently asked questions

### Is LLM SEO the same as GEO?

Yes, in practice. LLM SEO, GEO, AEO and LLM optimisation all describe getting a business named and cited in AI-generated answers. Only the emphasis differs.

### Does LLM SEO replace SEO?

No. Google says AI Overviews and AI Mode need a page that's indexed and able to show a snippet, with no extra technical requirements. LLM SEO adds AI crawler access, answer-first pages and outside mentions on top of that base.

### Do I need coding skills for LLM SEO?

Not for most of it. Answer pages and mentions need no code, but crawler rules, JavaScript rendering and schema need a developer or a team that edits your site.

### Can I block AI training and still appear in ChatGPT?

Yes. OpenAI says its crawlers work independently, so you can allow OAI-SearchBot for ChatGPT search and disallow GPTBot, which collects content for training. OpenAI says robots.txt changes take about 24 hours to apply to search.

### How do I know if ChatGPT mentions my company?

Ask it the questions your buyers ask, with search on, and record which brands it names and which pages it cites. Repeat them on a schedule, because answers change between runs, or use a visibility tool to automate this across several engines.

### What does an LLM SEO agency do?

An LLM SEO agency checks AI crawler access and builds answer pages for your buyers' questions. It also fixes your structured data and facts, earns mentions on the outside pages AI tools cite, and tracks named answers against enquiries. Ask what it ships each month.

### Is AI traffic in GA4 accurate?

Not always. Bot visits can land in GA4's AI-assistant channel and look like a surge, as in the client example above. Check the hour-by-hour pattern, devices and landing pages before you report AI traffic upward.

## What should you do next?

Write down five questions your best buyers would put to ChatGPT about your category. Ask them in ChatGPT, Gemini and Perplexity and note which companies they name, then check your robots.txt and firewall rules for OAI-SearchBot. If you'd like us to scope the LLM SEO work for your site, [let's talk pricing](https://www.searchmaxxed.com/contact).

REFERENCES

1. [guide to AI features](https://developers.google.com/search/docs/appearance/ai-features)
2. [crawler documentation](https://platform.openai.com/docs/bots)
3. [proposal itself](https://llmstxt.org/)

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