LLM SEO: what actually gets a business named by AI tools

LLM SEO has more opinions written about it than evidence. To separate the two, this guide draws on what practitioners and business owners reported in Reddit's SEO, local SEO, SaaS and small business communities through 2026: the tests they ran, what moved and what did not. Their numbers are self-reported and some posters were selling tools, so read them as field notes rather than proof. Where they agree, the pattern is worth acting on.

What is LLM SEO?

A large language model (LLM) is the software behind ChatGPT, Gemini, Claude and Perplexity. LLM SEO is the work of making those tools, and Google's AI Overviews and AI Mode, name your business when someone asks a question you should be the answer to.

It helps to know there are two ways these tools answer. Some answers come from what the model learned in training, which you cannot change on any timetable. Most commercial answers now come from a live search: the tool breaks the question into several smaller searches, reads the results and writes a summary with links. That second route is the one you can influence, and it is why practitioners who test both report the same thing: answers with search switched on can shift within weeks, while answers from memory alone hardly move.

LLM SEO is mostly the work of being on the pages an AI tool finds when it searches your buyer's question.

That is also why so much of it overlaps with ordinary search work. The GEO vs SEO guide sets out exactly where the two meet and where they part.

What do other sites have to do with it?

More than most owners expect. The most repeated finding in the threads is that "best" questions, such as "best kitchen fitter in Leeds" or "best CRM for small agencies", are answered from other people's pages: roundup articles, review sites, directories, forum threads and local press.

• A software founder in r/SaaS found his comparison pages won the prompts that named him alongside a competitor, but he was missing from every generic "best" answer. Those answers were built from third-party top ten lists and Reddit threads he did not appear in. Getting into a handful of those lists moved his visibility more than any change to his own site.
• A local SEO in r/localseo described a restaurant with more than 1,200 Google reviews at 4.8 stars, ranking on page one, that ChatGPT still passed over for a two-year-old rival. The rival had weaker reviews but coverage on food blogs and in Reddit threads.
• SE Ranking, an SEO tool company, posted a controlled test of a made-up brand on a new domain with supporting articles on other sites. The brand was named in about 16% of answers when one of those outside articles was among the sources, and in well under 1% when none was. It is a vendor's own study, but it points the same way as the owners' accounts.

The practical reading: if AI tools recommend a competitor, look first at which outside pages they cite, then at your own site. The guide to why ChatGPT recommends your competitor walks through that check.

Which of your own pages get cited?

Your site still matters, and the reports are consistent about which pages earn citations. They are the pages that answer one question completely, in plain words, near the top.

• Comparison and alternatives pages. A tool builder who logged around 2,150 cited links over two weeks found that "alternatives to X" questions cited comparison pages in roughly a third or more of cases, while "best X" questions almost never did.
• Prices. An SEO for a technical B2B supplier found that a forgotten product page with a price on it, no internal links and a weak title had been referenced by ChatGPT more than 200 times in Bing Webmaster Tools' AI reporting, more than any other product page. Commenters put it down to cost questions, which the page answered and others did not.
• Reviews in readable form. One local SEO published a client's Google reviews as a plain text page on the website. ChatGPT and Gemini began citing that page for "what do customers say" questions instead of directories.
• The exact question. A consultant asked a browsing AI tool the questions his best-ranking pages target and was cited on only two of eight. He was cited where he had a page for that exact question and missing where a competitor's roundup covered it, even when he outranked the roundup.

What did not work?

Three tactics come up again and again, mostly as disappointments.

• llms.txt files. An analysis shared in r/SEO of 30 days of server logs across 1,000 Adobe-hosted domains found the main AI crawlers never requested the file. Community polls on it were close to unanimous. Google lists AI text files among things you do not need. The llms.txt guide covers when one is still worth the ten minutes.
• Schema markup as a lever. In the larger datasets people shared, adding structured data barely changed AI citations. A study of hotels in Barcelona found AI appearances tracked ordinary SEO and review volume, with no effect from schema or llms.txt. A few single cases credit schema with fixing a wrong price in AI Overviews, which fits the view that it is useful hygiene, as the structured data guide explains, but not a growth tactic.
• AI content at volume. A junior SEO described a boss who pushed 10 to 50 AI-written articles a week until the blog received a Google manual action for scaled content. Google's spam policies name scaled content abuse directly.

Several owners also describe being invisible despite doing everything right on their own site: strong reviews, case studies, a clean technical audit. In each case the gap turned out to be off-site.

Does ranking on Google still matter?

Yes, for most businesses. The majority view among experienced practitioners is that AI tools search the web and lean on what ranks, so a site that cannot be found or crawled will not be quoted. A hotel study shared in r/SEO found some hotels missing from AI answers because they were poorly indexed on Bing or blocked OpenAI's search crawler.

The exceptions run both ways. There are reports of pages cited without ranking and pages ranking first without ever being cited. Treat ranking as the floor, not the finish: be crawlable by Google and Bing, allow the AI search crawlers (the guide to which AI crawlers to allow lists them), then work on the questions and sources above.

How do you know if it is working?

Carefully, because answers are unstable. One practitioner ran 3,837 calls to four AI providers and found the providers disagreed in more than half of the comparisons. Category leaders appeared almost every time; smaller brands swung wildly, appearing in over half of one tool's answers and a few percent of another's.

The habits people settle on:

• Run each question several times in a fresh session with memory off. One run is noise.
• Record which pages were cited, not only whether you were named. Cited pages are what you can act on.
• Check each tool separately. A gain in Perplexity says nothing about Google's AI Overviews.
• Ask "how did you hear about us?" as a free-text question. Much AI-referred traffic shows as "direct" in analytics, and buyers often type "ChatGPT" when asked.

The guide to tracking brand mentions in AI turns this into a monthly routine.

Is a citation worth anything?

Sometimes a great deal, sometimes nothing, and the threads are blunt about the difference. SE Ranking's test brand collected tens of thousands of citations and its server logs showed one single visit from an AI assistant. A three-month-old news site found around 700 of its pages cited but its name mentioned five times. One owner posted 797,444 AI Overview impressions that produced 7 clicks.

Against that, owners in law, finance and B2B software say the visitors AI tools do send convert well, though they are often only 1 to 3% of traffic. One SEO consultant traced a client worth close to $10,000 a month to a prospect who asked Claude for a recommendation. A car detailer noticed quote requests arriving as long lists of questions an AI tool had coached the buyer to ask.

The aim is to be named and correctly described for the few questions that lead to a sale, not to collect citations.

Where should an owner start?

1. Write down ten questions buyers ask before they hire someone like you, then put them to ChatGPT, Perplexity and Google, three runs each.
2. List every outside page the answers cite. Those are the lists, directories and reviews to get onto or correct.
3. Check you can be crawled. Google Search Console, Bing Webmaster Tools and your robots.txt file, in that order.
4. Publish the missing pages. Prices, comparisons, reviews and one page per important question, each answering in its first lines.
5. Repeat the same questions monthly and judge the trend over months, not a single good week.

If you would rather have this done once, properly, the AI visibility audit covers steps one to three for a fixed $700 and hands you the fix list, and the AI SEO services page explains how the ongoing work runs. If you are comparing providers, read what buyers report about hiring an AI SEO agency first. For the wider picture, start at the AI search visibility guide.