TL;DR: LLM SEO is the work of getting your brand named and cited in the answers that large language models (LLMs) like ChatGPT, Claude, Gemini and Perplexity give. It builds on classic SEO and adds measuring what the models say, so you know which questions to win and which pages to get onto.
What is LLM SEO?
LLM SEO means optimizing for the answers LLMs write, where classic SEO optimizes for a ranked list of links. A buyer asks "what's the best CRM for a small agency", the model writes an answer, and a few brands get named in it. LLM SEO is the work of being one of them.
It goes by other names, like AEO (answer engine optimization), GEO (generative engine optimization) and AI SEO. These are all basically the same thing. If you want the longer breakdown, AEO vs GEO vs SEO covers the three terms, GEO vs SEO covers what changes from classic search, and AEO vs SEO does the same for the answer engine side.
LLM SEO compared with classic SEO, AEO and GEO
| Classic SEO | LLM SEO | AEO | GEO | |
|---|---|---|---|---|
| Goal | Rank a page | Get named in an LLM answer | Get named in an answer | Get named in a generated answer |
| Where it shows up | Search results page | ChatGPT, Claude, Gemini, Perplexity | AI answers and AI Overviews | AI answers and AI Overviews |
| Measured by | Position and clicks | Mentions and citations | Mentions and citations | Mentions and citations |
| Off-site lever | Backlinks | Mentions on pages the models read | Mentions on cited pages | Mentions on cited pages |
| Content shape | Long and comprehensive | Direct and easy to quote | Direct and easy to quote | Direct and easy to quote |
The 3 right-hand columns are generally the same job. Classic SEO is the one that differs.
What LLM SEO involves
Keywords in SEO become questions in LLM SEO, and backlinks become mentions. The core work stays the same: pages a crawler can read, content that matches what people are asking, and a reputation outside your own site.
The parts that are specific to LLMs:
- Measure the answers. Ask the questions your buyers ask and record who gets named. Peak Answer does this across the major engines, and the AEO tracker shows how mentions change over time.
- Get onto cited pages. LLMs build answers from pages they retrieve. Being listed on those pages often does more than publishing your own.
- Write answer-first. Put the direct answer in the first paragraph, use clear headings, and add comparison tables and FAQs.
- Let the bots in. AI crawlers need to be able to read your pages. The AI crawler checker shows which ones your robots.txt allows.
- Add an llms.txt. It is a plain file that points models to your key pages. The llms.txt generator builds one for you.
For a quick read on where you stand, the AEO checker scores a page, and the AI visibility audit asks real buying questions and shows who gets named.
How many cited sites block AI crawlers?
Peak Answer checked the robots.txt files of sites that were cited in answers for 15 tech niches.
What was measured. 1,540 cited URLs across 847 domains and 887 hosts. The cited domains came from ChatGPT answers, Google organic results and Google AI Overviews. 403 of the 847 domains were cited by ChatGPT, and 444 were cited only by Google. Each host's own robots.txt was tested against the cited path, following RFC 9309.
Headline blocking rates. The denominator is 818 domains whose robots.txt was readable or absent. A missing robots.txt counts as allowed. "Blanket" means the whole site is disallowed for that crawler.
| Crawler | Domains blocking | Share | Blanket blocks |
|---|---|---|---|
| GPTBot | 24 of 818 | 2.9% | 17 |
| ClaudeBot | 20 of 818 | 2.4% | 14 |
| ChatGPT-User | 14 of 818 | 1.7% | 11 |
| Google-Extended | 14 of 818 | 1.7% | 12 |
| OAI-SearchBot | 12 of 818 | 1.5% | 8 |
| PerplexityBot | 11 of 818 | 1.3% | 8 |
| Bingbot | 3 of 818 | 0.4% | 1 |
| Googlebot | 2 of 818 | 0.2% | 1 |
Among the 394 domains cited by ChatGPT, 9 (2.3%) blocked GPTBot and 4 (1.0%) blocked OAI-SearchBot. Among the 424 cited only by Google, 15 (3.5%) blocked GPTBot and 8 (1.9%) blocked OAI-SearchBot.
Other numbers from the same run:
- 15 of 784 domains with a readable robots.txt (1.9%) blocked GPTBot and allowed OAI-SearchBot.
- 483 of 809 domains (59.7%) had an llms.txt file.
- 1,290 of 1,540 URLs (83.8%) returned a real page. 123 (8.0%) returned a bot-challenge page, and 98 (6.4%) were skipped because the site's robots.txt disallowed Peak Answer's own crawler.
Caveats. The sample is tech sites only. robots.txt, llms.txt and page content were read on the day of the check, not on the day each URL was cited, so rules may have changed in between. Pages were fetched without JavaScript. Cells with a denominator under 10 are flagged in the report. These numbers describe what was found. They do not show that blocking or allowing a crawler changes whether a site gets cited.
Where to start
- Run the AI crawler checker on your domain.
- Generate an llms.txt with the llms.txt generator.
- Score your key pages with the AEO checker.
- Run the AI visibility audit to see which buying questions name you and which name someone else.
- Track those questions over time with the AEO tracker.
FAQs
Regular SEO aims to rank a page in a list of links. LLM SEO aims to get your brand named in the answer a language model writes. The technical groundwork is shared, and the main additions are measuring the answers and getting mentioned on the pages the models read.
Basically yes. They are different names for getting named in AI-generated answers. The posts on AEO vs GEO vs SEO and GEO vs SEO go through the terms.
It is a quick file to add, and 483 of 809 domains (59.7%) in the crawler access data already had one. The llms.txt generator builds it in a minute.
Check your robots.txt for GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot and PerplexityBot. The AI crawler checker does this for you and shows which crawlers are allowed or blocked.