LLM SEO, what it is, what works and what to avoid

What is LLM SEO?

LLM SEO means improving how large language models talk about your business. LLM stands for large language model, the technology behind ChatGPT, Gemini, Claude, Copilot and the models inside Perplexity. You will also see it called SEO for LLMs, LLM optimization, AI SEO or generative engine optimization. They all describe the same work.

The aim is practical. When a buyer asks an AI tool for advice in your field, you want to be named, described correctly and linked. When they ask about you directly, you want the answer to be accurate and fair.

Which LLMs matter most for US businesses?

ChatGPT is the chatbot the most Americans have used, but it is not the only one worth checking. Pew Research Center's 2026 survey of 5,119 US adults found 44% have used ChatGPT. It also found Gemini at 24%, Copilot at 17%, Meta AI at 14% and Grok at 8%.

The worldwide numbers point the same way. OpenAI says ChatGPT has more than 900 million weekly active users. In July 2026, Alphabet said the Gemini app has 950 million monthly active users, and that AI Mode in Google Search had passed 1 billion.

For many US brands, that means ChatGPT and Google's AI features first, then Gemini, Copilot and Perplexity. B2B companies may want to check Copilot early too.

How is LLM SEO different from traditional SEO?

LLM SEO changes what you measure and where you work. Traditional SEO tracks rankings, impressions and clicks for pages on your site. LLM SEO tracks whether a model mentions you, where in the answer, in what tone, and which sources it relies on.

The work also reaches further. A model's view of your business comes partly from your site and partly from everything else written about you. Reviews, directories, news stories, comparison articles and Reddit threads all feed in. The basics of SEO still apply, and they matter a great deal. The full comparison is in GEO vs SEO.

How do large language models learn about a business?

Models learn about a business in two ways. One is training, which happens months before you use the model. The other is live search, which happens when you ask a question.

Training. A model is trained on a very large collection of public text. If your business was written about widely and consistently, the model will have a fair picture of you. If you were barely mentioned, it may know little and fill the gaps with guesses.

Live search. Many AI tools now search the web before they answer. They read the pages they find and write an answer based on them. Here, your current pages and listings matter directly. OpenAI says ChatGPT search rewrites your question into targeted queries, may use an approximate location from your IP address, and may share location with trusted providers for things like nearby business listings.

Different crawlers serve these two routes. The table shows the main ones named in each company's own documentation.

This matters when you edit robots.txt. OpenAI says sites that block OAI-SearchBot will not be shown in ChatGPT search answers, apart from navigation links. Blocking GPTBot, by contrast, only affects training. Anthropic describes a similar split in its crawler help article. The detail is in AI crawlers and robots.txt.

Why do ChatGPT, Gemini and Claude say different things about the same business?

Each tool has its own model, its own training data and its own way of searching. So it is normal for ChatGPT to name you while Gemini does not, or for Claude to describe an older version of your business.

The sources they lean on also differ. Yext studied 6.8 million AI citations from 1.6 million queries across ChatGPT, Gemini and Perplexity in July and August 2025. It found 86% of citations came from sources brands control. First-party websites made up 44% and listings 42%. Gemini favored websites, at 52.1% of its citations, while OpenAI leaned on listings, at 48.7%.

In practice, that means your own site and your listings both need to be right. New data deals shift things further. In July 2026, Search Engine Land reported that OpenAI and Yelp agreed a deal giving ChatGPT access to Yelp reviews, ratings, photos and business details. For a restaurant, a plumber or a med spa, the Yelp profile is now part of what ChatGPT can see.

Timing and wording play a part too. A model trained some time ago may not know about a new location or a change of name. "Best CPA in Denver" and "affordable CPA for freelancers near Denver" can bring back different firms from the same tool. That is why one check in one tool proves little.

Is LLM SEO a scam?

LLM SEO is not a scam, but the label attracts some poor offers. The underlying work is real. It is SEO, content, PR and reputation, measured in a new place.

These warning signs suggest an offer is overselling.

• A guaranteed ranking in ChatGPT. AI answers change from run to run. No one can promise a fixed spot.
• A secret prompt or trick. What you type into your own ChatGPT account does not change the answers other people get.
• Submitting your site to ChatGPT. There is no submission form. Search-enabled tools find pages by searching and crawling.
• One file that fixes everything. An llms.txt file or a schema block can help a little, but neither will make an unknown brand appear.
• Fake reviews or planted Reddit posts. These break platform rules and can do lasting harm when they are found.
• Hundreds of AI-written pages. Google warns that generating many pages without adding value may break its spam policy on scaled content abuse.

A sound offer explains how visibility will be measured, shows the sources engines cite, and admits that results are a trend and not a promise.

Does llms.txt help with LLM SEO?

llms.txt is optional and its effect is limited. It is a proposed standard from 2024 for a plain markdown file that gives AI tools a clean summary of a site. Some tools read it. The large AI companies say little about it in their public crawler documentation.

Google says there are no special files or markup needed for its AI features. So treat llms.txt as a tidy extra, not a ranking factor. The llms.txt guide covers when it is worth adding.

What LLM SEO work actually helps?

The work that helps is mostly the same work that builds a strong brand online. Here is where it tends to pay off.

1. Keep your facts consistent everywhere. Name, address, phone, services, hours and locations should match across your site, Google Business Profile, Bing Places, Apple Business Connect, Yelp and BBB.
2. Make key pages easy to quote. Answer the main question in the first sentence under each heading. Use specific facts, dates and named authors.
3. Describe your business in structured data. Organization or LocalBusiness markup, with links to your official profiles, helps models connect the dots.
4. Earn mentions on sites the engines cite. Industry directories such as Avvo or Healthgrades, review sites, local news and comparison articles all count.
5. Take part openly in communities. Reddit threads are often cited. Helpful answers from a named staff member can be worth more than an ad.
6. Let the right crawlers in. Check robots.txt, your CDN and any firewall rules for search bots you did not mean to block.
7. Fix what is wrong. If an AI answer gets a detail wrong, trace it to the page that says it and correct that page.

The research backs the content side. In the GEO research paper, adding citations, quotations and statistics raised source visibility by up to 40% in the authors' benchmark. Local businesses will find more on listings and reviews in AI search for local businesses.

Why does LLM SEO matter for revenue?

Visits from AI tools can be good visits. Adobe reported that traffic from AI sources to US retail sites grew 393% year over year in the first quarter of 2026. In March 2026, that traffic converted 42% better than non-AI traffic.

That is retail data, so it will not match every business. It is still a useful sign that AI visits are worth tracking, alongside mentions in the answers themselves.

Who should own LLM SEO in a business or agency?

LLM SEO works best with whoever already owns SEO and content, with help from PR and customer service. The skills overlap, and splitting the work tends to leave gaps.

PR matters because third-party coverage shapes what models say. Customer service matters because reviews and replies feed into answers. Someone also needs to own the facts, such as prices, locations and services, so they stay the same everywhere.

For a 15-location franchise, that often means a central marketing team owns the facts and each franchisee keeps its own listings current. For an agency, it often fits inside the SEO retainer, with AI answers added to the monthly client report.

How do you measure LLM SEO?

You measure it by asking the engines the same set of buyer questions on a schedule and recording what comes back. Track mentions, position in the answer, sentiment, competitors named and cited pages.

It helps to separate the two routes. Asking a model without web search shows what it learned in training. Asking with web search shows what it finds today. If a model knows nothing about you without search but names you with search, your live pages are doing the work. If it names you without search but gets details wrong, older content is shaping its view.

How Axiom GEO helps

Axiom GEO asks ChatGPT, Perplexity and Gemini with web search on, so their answers name the pages they used. Claude is asked without web search, which shows how the model sees your brand from what it already knows. That gives you both routes side by side. AI crawler analytics reads your server logs to show which AI bots visit, how often and which pages. The entity audit checks the entity graph your site publishes in structured data and returns scored fixes. The Professional plan covers all four engines at £799 a month, billed in pounds sterling, and the pricing page shows an approximate US dollar figure. Axiom GEO is run from the UK and works for US brands and agencies.