LLM SEO: What It Is, How It Differs From SEO, and What Works

LLM SEO is the work of getting large language models, such as ChatGPT, Perplexity, Google AI Overviews and AI Mode, to name your brand and cite your pages when people ask them questions. It builds on normal SEO, because most of these tools search the web before they answer, and it adds two things SEO never measured: whether your brand is named in the answer, and what the rest of the web says about you.

This guide covers what LLM SEO is, how it relates to SEO, AEO and GEO, how language models decide what to say, and which tactics have evidence behind them.

What is LLM SEO?

In classic SEO, success is a position in a list of links. In LLM SEO, success is being part of a single written answer. When someone asks "what's the best CRM for a five-person sales team", the model names a few products and links a few sources. LLM SEO is everything you do to be one of them.

Some people use "LLM SEO" to mean using ChatGPT to do SEO tasks. That's a different topic, which we touch on below under "Can ChatGPT do SEO?".

How does LLM SEO relate to SEO, AEO and GEO?

The names overlap, and the industry hasn't settled on one:

  • SEO (search engine optimization): ranking pages in search results. Measured by position and clicks.
  • AEO (answer engine optimization): being the answer rather than one of the links. The term predates generative AI, from featured snippets and voice search, and now covers AI answers too.
  • GEO (generative engine optimization): optimizing for engines that generate answers. The term comes from a 2023 research paper by Aggarwal and colleagues, later accepted to KDD 2024.
  • LLM SEO, LLMO, AI SEO, AI search optimization: different names for the same goal.

In practice, LLM SEO, GEO and AEO describe the same work. The differences that matter aren't between the names. They're between LLM SEO and classic SEO:

  1. The unit of success is a mention or a citation, not a rank. You're either in the answer or you're not.
  2. Answers vary from run to run. In SparkToro's research on 2,961 responses, ChatGPT and Google's AI gave the same brand list less than once in 100 runs of the same prompt. You measure how often you appear, not where.
  3. Other sites' words about you count directly. A model can name you because a review site or a Reddit thread did, even if it never cites your site.
  4. Models use passages, not pages. The answer quotes or paraphrases a paragraph. A page with one clean answer can beat a longer page with a buried one.
  5. Each engine has its own index. Google's AI features draw on Google. ChatGPT's citations track Bing closely.

How do LLMs decide what to say?

A language model answers from two places.

Memory. Everything the model learned in training. If plenty of pages described your brand before the model's cutoff, it can name you with no search at all. You can't edit this directly. It shifts slowly, as more of the web writes about you and newer models are trained on it.

Retrieval. For many questions, the tool searches first, reads a few pages and writes its answer from them, citing them as sources. Google says AI Overviews and AI Mode may use "query fan-out", running multiple related searches across subtopics for one answer. ChatGPT runs its own search, and only sites that let OpenAI's search crawler in can show up in it, per OpenAI's documentation.

That gives LLM SEO two levers. Retrieval is the faster one: rank in the sources each engine searches and have the best passage there. Memory is the slower one: be written about, consistently, on many sites.

What actually moves LLM SEO?

Here is what has evidence behind it, roughly in order of impact.

1. Being readable by each engine's crawler

Each engine has its own crawler, and blocking it removes you from that engine's live answers:

  • ChatGPT: OAI-SearchBot. Blocking GPTBot, OpenAI's training crawler, does not affect search.
  • Google AI Overviews and AI Mode: Googlebot. Google says robots.txt rules for Googlebot are the control for Search. Google-Extended is a separate token for some of Google's other AI systems, and it doesn't take you out of AI Overviews.
  • Perplexity: PerplexityBot.

Check robots.txt, then check your CDN or firewall. Cloudflare changed its default to block AI crawlers in July 2025, so check the setting even if you never touched it.

2. Ranking in the search results each engine draws on

Retrieval-based answers mostly cite pages that already rank:

  • Google AI Overviews: in Ahrefs' study of 1.9 million citations, 76.1% of cited pages ranked in Google's top 10.
  • ChatGPT: Seer Interactive found 87% of ChatGPT's citations matched Bing's top organic results for the same question, in a sample of about 100 questions.
  • Google versus the assistants: across 15,000 long-tail prompts, Ahrefs found that only 8% of ChatGPT's in-text citations ranked in Google's top 10 for the prompt, against 28.6% for Perplexity.

So classic SEO is the base of LLM SEO, but for ChatGPT, Bing deserves as much attention as Google.

3. Passages that answer the question with specifics

The GEO paper tested what changes make a page more visible in generated answers. Adding quotations, statistics and cited sources gave the biggest gains, a relative improvement of 30% to 40% in the authors' benchmark. Keyword stuffing did worse than leaving the page alone. The pattern holds up in practice:

  • Put the question in a heading and the answer in the first sentence under it.
  • Name the subject in each key sentence, so a passage still makes sense lifted out of the page.
  • Give facts a model can attribute: prices with dates, limits, named steps, numbers with their source.
  • Publish facts only you have, like your own data, tests or benchmarks.

4. Mentions on other sites

For brand mentions, what other sites say may matter more than links. In Ahrefs' study of about 75,000 brands, branded web mentions had the strongest correlation with being named in AI Overviews (0.664), against 0.218 for number of backlinks. It's a correlation, and it covers Google only, but it lines up with where AI answers get their brand names: list articles, reviews, forums and news.

Backlinko calls the deliberate version of this LLM seeding: publishing in the formats and places models read, such as "best of" lists, comparison pages, review platforms and community threads.

5. Consistent facts about your brand

Models combine what many pages say. If your site, LinkedIn page, review profiles and directory listings describe you in different words, with different categories and prices, the model gets weak and conflicting signals. Write one sentence that says what you are, who it's for and what it costs, and use it everywhere.

6. Current pages

Keep prices, steps and screenshots up to date, and show a real "last updated" date. Questions about products and prices depend on current facts, so stale pages cost you exactly where buyers are deciding.

What doesn't move it

  • llms.txt files. Google says you "don't need to create new machine readable files, AI text files, or markup" for AI Overviews or AI Mode. OpenAI's crawler documentation doesn't mention llms.txt either. It's harmless, but it isn't a strategy.
  • Special schema. Google says there's no special structured data for its AI features. Schema still helps with rich results, but only when it matches what's visible on the page.
  • Keyword stuffing. It lost visibility in the GEO paper's tests.
  • Hidden instructions aimed at AI. Text written to manipulate models, hidden from readers, is hidden-text spam by Google's rules and a risk everywhere else.
  • Tracking a single "rank" in ChatGPT. Given how much answers vary, a position in one answer is mostly noise.

How do you measure LLM SEO?

  1. Build a question set. Write 20 to 50 questions buyers ask before buying, without your brand name.
  2. Ask each engine, more than once. Use a clean session and repeat each question on different days.
  3. Record four things per answer: named or not, cited or not, who was named instead, and which URLs were cited.
  4. Report rates. Mention rate and citation rate per engine, per month.
  5. Add first-party data. Visits from chatgpt.com and perplexity.ai in your analytics; Bing Webmaster Tools' AI Performance report for Copilot and Bing citations; Search Console, which counts AI Overview and AI Mode traffic inside the Web search type.

For engine-by-engine steps, see how to rank in ChatGPT and how to rank in AI Overviews.

Is SEO being replaced by AI?

No. The AI answers sit on top of search indexes: Google's features draw on Google's results, and ChatGPT's citations track Bing's. What's changing is the value of a click. In Pew Research's March 2025 data, people clicked a regular result on 8% of Google visits that showed an AI summary, against 15% when there was none. Ranking still matters. Being named in the answer above the links matters more than it used to.

What is AI SEO called now?

There's no single name. GEO, AEO, LLM SEO, LLMO and AI search optimization are all in use for the same work: getting AI answers to name and cite you. Pick whichever term your team understands and measure the same things either way.

Can ChatGPT do SEO?

Partly. It's useful for outlines, question research, rewriting a section to answer first and writing schema markup. It can't see your Search Console data, crawl your whole site or publish on a schedule. Google's guidance on AI-generated content allows AI-assisted pages that help readers, and warns that mass-producing pages "without adding value for users" counts as scaled content abuse. An AI SEO agent connects the parts: keyword research, a site audit, writing, publishing and tracking AI answers, on a schedule you can read in a dashboard.

Which AI tool is best for SEO?

It depends on the job. Dedicated AI visibility trackers such as Profound, Peec AI and Otterly can measure more prompts across more engines, and they're the better choice if you only want reports. SEO suites such as Ahrefs and Semrush have added AI tracking on top of their keyword data. Agents like Bottally track four engines and also write and publish the content that closes the gaps. We compare the options in our list of the best AEO tools.

An LLM SEO checklist for the next 30 days

  1. Check robots.txt and your CDN for OAI-SearchBot, Googlebot and PerplexityBot.
  2. Verify your site in Bing Webmaster Tools and submit your sitemap.
  3. Write 20 buyer questions without your brand in them.
  4. Ask each one in ChatGPT, Perplexity, AI Overviews and AI Mode, and record who's named and what's cited.
  5. For each question, list the cited third-party pages you're missing from, and contact the top three.
  6. For each question with no good page on your site, publish one that answers it in the first sentence.
  7. Write your one-sentence brand description and use it on every profile.
  8. Re-run the questions at the end of the month and compare rates.

See where you stand

Steps 3 and 4 take an afternoon by hand. The AI visibility checker does them for you: it puts your buyer questions to ChatGPT, Perplexity, Google AI Overviews and AI Mode, and shows if each answer names or cites you, who it names instead, and the sources behind it. If you want 30 questions tracked every week and an article published every day aimed at the gaps, see Bottally Pro pricing.