How to Get Cited by ChatGPT and Perplexity

Getting cited by ChatGPT and Perplexity comes down to three levers with real evidence behind them: let their search crawlers reach your pages, write passages that can be lifted out and quoted on their own, and make it unambiguous who you are and what you are describing. Schema markup and llms.txt files are not on that list – the best controlled data available says neither reliably moves citations. This piece documents how each assistant retrieves sources, what the evidence does and does not support, and how I check my own site’s AI-referral traffic, including where it stands right now.

Most “how to get cited by AI” advice is a repackaged SEO checklist with new acronyms stapled on. Some of it holds up. Some of it – schema markup for citations, llms.txt as a control file – does not survive contact with the data. Here is what OpenAI and Perplexity document about how their assistants find and cite sources, what controlled studies say about the tactics that do not work, and a routine for checking where your own site stands.

How ChatGPT and Perplexity actually retrieve sources

Both companies publish this. You do not need to guess.

OpenAI runs three separate crawlers and treats them as independently controllable. Per its own crawler documentation, OAI-SearchBot is “used to surface websites in search results in ChatGPT’s search features. Sites that are opted out of OAI-SearchBot will not be shown in ChatGPT search answers” – the crawler that matters for citations. ChatGPT-User fires only when someone asks ChatGPT to look at a specific page, not as a background indexing pass. GPTBot exists solely “to crawl content that may be used in training,” unrelated to citations. OpenAI states plainly that these are independent: “a webmaster can allow OAI-SearchBot in order to appear in search results while disallowing GPTBot.” So blocking “the AI bots” as one group in robots.txt is a mistake for anyone who wants ChatGPT citations – blocking OAI-SearchBot removes you from ChatGPT search answers; blocking GPTBot only opts you out of training data.

Perplexity draws the same line, with one wrinkle. Its developer docs describe PerplexityBot as “designed to surface and link websites in search results on Perplexity. It is not used to crawl content for AI foundation models” – the citation-relevant crawler. Perplexity-User fires when “users ask Perplexity a question” and it “might visit a web page to help provide an accurate answer.” The wrinkle: PerplexityBot “respects robots.txt rules,” but Perplexity-User “generally ignores robots.txt rules” because a real person’s request triggered it. Block PerplexityBot entirely and you opt out of citations, not just training.

The three levers, ranked by evidence strength

Crawler access is the strongest-evidence lever: it is not inferred, it is stated directly in the documentation quoted above. Check robots.txt for OAI-SearchBot and PerplexityBot specifically, not a blanket “AI bot” rule.

Extractable structure is moderate evidence: it follows from how these assistants describe fetching and quoting passages, not a controlled experiment isolating structure. A direct-answer paragraph near the top, a real question answered in a heading, and prose that stands alone as an answer are easier to lift cleanly. This is the same logic behind AEO generally – as I have written elsewhere on this site, answer engine optimization is “the practice of making your content a source that AI assistants such as ChatGPT, Perplexity, and Google’s AI Overviews cite when they answer your buyers’ questions.”

Entity clarity is the weakest evidence of the three: anecdotal, not a controlled result. A retrieval system still has to resolve who or what a page is about before citing it as an authority, and a page that never states its own subject, author, or organization gives it less to work with. I could not find a controlled study isolating entity clarity the way the schema study below isolates markup, so treat this as a plausible mechanism, not a proven lever.

What does not work: the schema and llms.txt hype

Two tactics get pitched constantly as AI-citation levers, and the best available evidence does not support either.

Schema markup is the first. I already covered the controlled test on this site in detail: Ahrefs ran a difference-in-differences comparison, tracking “1,885 pages that added JSON-LD structured data” against “4,000 matched control pages that did not,” and found “statistically insignificant moves for ChatGPT and Google AI Mode, and a significant decline for Google AI Overviews.” Schema still earns Google rich results and is worth keeping for that. It is not, on this evidence, a lever for AI citations.

llms.txt is the second, and the evidence against it is more direct. Ahrefs analyzed crawler logs from 137,000 domains and, per Search Engine Journal’s coverage, found “97% of llms.txt files got zero requests” during the study period – and of the small remainder that got any traffic, AI retrieval bots tied to ChatGPT and Perplexity accounted for only about 1% of those requests. The assistants documented above retrieve pages directly, the same way a search crawler does. Neither company’s crawler documentation mentions llms.txt as an input. Publishing one is not harmful, but current data gives no reason to expect it to move citations.

A weekly citation-check routine you can copy

I run this same check on this site on a schedule, using nothing most sites do not already have. First, in GA4, check whether the native “AI Assistant” default channel group is populated – Google added it to recognize referral sessions from ChatGPT, Gemini, and other assistants automatically, and I have written up the full setup and fallback method separately if your property is not showing it yet. Second, spot-check robots.txt weekly for OAI-SearchBot and PerplexityBot specifically, since a CDN or security-plugin update can silently add either to a blocklist. Third, ask each assistant a question your content should answer and note whether it cites you, a competitor, or nothing – manual and not scalable, but the only direct signal available, since neither company publishes a citation-tracking API.

This site’s own citation status, stated plainly

Here is where this site actually stands, checked the same way I am recommending you check your own: pulling the GA4 “AI Assistant” default channel group for the trailing 30 days. Over that window, this property recorded 95 Direct sessions, 5 Organic Search sessions, and 2 Unassigned sessions – zero sessions attributed to the AI Assistant channel. That is not a claim this site never gets an AI citation; it is what the measurement shows right now, on a small, young site. I would rather publish that honestly than imply a result I cannot back up. If it changes, the routine above is how I will catch it.

What is documented here versus inferred

The crawler-behavior quotes above come directly from OpenAI’s and Perplexity’s own developer documentation, fetched and verified live on the date of writing, not third-party interpretation. The schema-markup finding and the llms.txt traffic figures are both independently run Ahrefs studies. Entity clarity, as noted above, is the one claim here that is plausible reasoning rather than a controlled result, labeled that way rather than dressed up as proven. There is no search-volume figure in this piece for “how to get cited by ChatGPT” – Keyword Planner access is not functional in my environment, and I would rather say so than guess.

Frequently asked questions

Does blocking AI bots in robots.txt stop training but not citations?

It depends which bot you block. OpenAI’s own documentation confirms GPTBot, OAI-SearchBot, and ChatGPT-User are controlled independently in robots.txt: disallowing GPTBot only opts a site out of AI training data, while disallowing OAI-SearchBot removes it from ChatGPT search answers entirely. Perplexity works the same way, with PerplexityBot as the citation-relevant crawler. A blanket rule that blocks every bot with “AI” or “GPT” in its name will usually remove you from citations, not just training.

Does adding an llms.txt file help get my site cited by ChatGPT or Perplexity?

The available evidence says no. Ahrefs’ analysis of crawler logs across 137,000 domains found that 97% of published llms.txt files received zero requests, and AI retrieval bots tied to ChatGPT and Perplexity made up only about 1% of the requests that did occur. Neither OpenAI’s nor Perplexity’s own crawler documentation lists llms.txt as something their citation-relevant crawlers read.

Does schema markup increase how often AI engines cite a page?

A controlled Ahrefs study comparing 1,885 pages that added JSON-LD schema against 4,000 matched pages that did not found statistically insignificant movement for ChatGPT and Google AI Mode citations, and a statistically significant decline for Google AI Overviews. Schema is still worth adding for Google rich results, but current evidence does not support it as an AI-citation lever.

For the fuller first-party definition of AEO this piece builds on, a practical intro to answer engine optimization for B2B SaaS covers that in depth. The schema-markup study referenced above is broken down fully in does schema markup help AI citations. For the exact GA4 setup behind the citation-check routine in this piece, see how to track AI referral traffic in GA4. If you want the broader terminology this piece sits inside, GEO vs SEO vs AEO and what an AI SEO agent actually is both cover adjacent ground.

---