LLM Brand Visibility: How AI Models Decide What to Say About You

LLM brand visibility is whether, and how accurately, AI models such as ChatGPT, Claude, Gemini and Perplexity mention your brand when people ask about your category. It is decided in four stages run by different systems: what the model memorized in training, whether its crawler can reach your site, whether your page is retrieved for this particular question, and whether the model uses and cites it.

Only the second stage is fully in your hands. This piece walks through each stage across vendors, using the operators' own documentation (opened October 16, 2026) and the studies that tested them, then shows how to measure visibility without averaging things that should never be averaged.

The four stages at a glance

Most GEO advice treats an AI answer as one decision. It is a pipeline, and a July 2026 survey of 45 GEO studies describes it the same way: "a stochastic, partially observable pipeline spanning search activation, crawling and indexing, retrieval, reranking and context allocation, citation" and beyond (arXiv:2607.14035).

Stage	What happens	Web search	Who controls it	What you can do
1. Memory	The model answers from what it learned before its training cutoff	Off	The model vendor	Nothing that lands before the next model
2. Access	A crawler fetches your page and an index stores it	On	You and your CDN	robots.txt, firewall, raw HTML, snippet directives
3. Retrieval	Rewritten queries pull candidate pages for this question	On	The search operator	Be the relevant answer to the question
4. Generation	The model writes, draws on some sources, cites some	On	The model	Keep your facts correct and consistent

The survey's conclusion is the sentence to keep in mind for everything below: "already-retrieved content can causally alter its citation or use, but no reviewed technique shows a stable, longitudinal, cross-platform causal effect on organic discoverability or downstream behavior." Nearly every published GEO effect is a stage-four result, measured on pages already in the model's context.

Search on or off: the split behind every answer

Most platforms decide, question by question, whether to search the web at all. That one switch decides whether stages two to four happen, and it is rarely visible to the person asking.

Platform	Who decides to search	What the vendor says
ChatGPT	The model, or the user picks Search	"ChatGPT may search the web automatically when your question would benefit from current information" (OpenAI)
Claude API	The model, steered by the developer	"Claude determines when to search based on the prompt"; "Triggering is steerable through your system prompt" (Anthropic)
Claude app	A toggle, or the model in the new Claude experience	"there's no web search toggle"; "Claude searches the web when it helps" (Claude Help Center)
Gemini API with Google Search	The model	The model "determines if a Google Search can improve the answer" (Google AI for Developers)
Perplexity	Built around search	It can "search the internet in real-time" (Perplexity)
Google AI Overviews	Google, per query	Shown only when "additive to classic Search, and as such, often don't trigger" (Google Search Central)

The consequence: any single "AI visibility" number blends memory answers and search answers in a ratio nobody observed. Ask which mode produced a result before you act on it.

Stage 1: what the model already believes

With search off, a model answers from weights frozen at a cutoff. As of October 2026, OpenAI lists an "Apr 30, 2026" cutoff for its flagship GPT-6 Astra, "May 18, 2026" for GPT-6 Luna, and Apr 20, 2026 for chat-latest, the Instant model used in ChatGPT, which "will be regularly updated." Several knowledge dates from one vendor, and OpenAI does not say which model answered a given ChatGPT question.

The only path into a future model is the training crawl, and every vendor names a separate crawler for it. OpenAI says GPTBot crawls content "that may be used in training"; Anthropic says ClaudeBot collects content "that could potentially contribute to their training"; Google-Extended controls whether content may be used "for training future generations of Gemini models" and for grounding in Gemini Apps and Grounding with Google Search on Vertex AI, so blocking it is not only a training decision.

No vendor claims that allowing a training crawler improves how its model describes you, and no study has measured it. The honest label is unmeasured. A wrong fact in a memory answer stays until a newer model ships.

Stage 2: whether a crawler can reach you

This is the only stage where the publisher owns every variable and the operators document the consequence. Each vendor splits its bots by job, and blocking the wrong one is the most common self-inflicted error.

Vendor	Search or index crawler	Fetcher triggered by a user	Training crawler
OpenAI	OAI-SearchBot	ChatGPT-User: "robots.txt rules may not apply"	GPTBot
Anthropic	Claude-SearchBot	Claude-User	ClaudeBot
Perplexity	PerplexityBot	Perplexity-User: "generally ignores robots.txt rules"	None; Perplexity says neither bot is used for training
Google	Googlebot	Google-Agent, Gemini Notebook and other user-triggered fetchers: "generally ignore robots.txt rules"	Google-Extended (a robots.txt token, not a separate crawler; also governs Gemini Apps and Vertex AI grounding)
Meta	Meta-WebIndexer	Meta-ExternalFetcher: "may bypass robots.txt"	Meta-ExternalAgent

Sources: OpenAI, Anthropic (updated April 7, 2026), Perplexity, Google, Meta.

The consequences are stated plainly. Blocking OAI-SearchBot means you "will not be shown in ChatGPT search answers"; blocking Claude-SearchBot "may reduce your site's visibility and accuracy in user search results." OpenAI and Perplexity recommend allowing their search crawlers so your site appears in their results, and Meta states the link most directly: "Allowing Meta-WebIndexer in your robots.txt file helps us cite and link to your content in Meta AI's responses."

robots.txt is necessary, not sufficient. OpenAI requires that your host or CDN "allows traffic from OpenAI's published searchbot IP addresses", Perplexity tells firewall users they "may need to explicitly whitelist" its bots, and Anthropic warns that IP blocking "impedes our ability to read your robots.txt file." A firewall that returns 403 to a bot your robots.txt allows is a silent, total failure.

Two more gates sit on the page itself. Vercel found ChatGPT's and Claude's crawlers fetch JavaScript but "don't execute them" (Vercel, December 2024), so facts that appear only after scripts run are invisible to them. And snippet directives remove content: Google says nosnippet "will also prevent the content from being used as a direct input for AI Overviews and AI Mode", and Bing says data-nosnippet content is "excluded from snippets and AI summaries" (Bing, October 15, 2025).

Stage 3: whether your page is retrieved for this question

No engine searches with the question as typed. OpenAI says ChatGPT search "typically rewrites your query into one or more targeted queries"; Google's AI features may use "query fan-out", issuing related searches across subtopics; the Gemini API "automatically generates one or multiple search queries and executes them." The input that decides retrieval is one you never see.

In the consumer apps you never see them. The Gemini, OpenAI and Perplexity APIs return the queries run for your own API calls, and Bing Webmaster Tools' AI Performance report shows grounding queries, "the key phrases the AI used when retrieving content that was referenced in AI-generated answers", for Microsoft Copilot, Bing's AI summaries and "select partner integrations" (Bing, February 10, 2026). Microsoft notes the data "represents a sample of overall citation activity."

Once candidates are pulled, two things dominate in the research. The survey above calls "topical relevance and context position" the most reproducible levers, and a 252,000-trial lab study found "topical relevance and list position are the biggest drivers of being cited first" (arXiv:2605.25517). Position inside an engine's candidate list is set by the operator, not by you.

Relevance is not keyword coverage. Google says its AI systems "can understand synonyms and general meanings", so "you don't have to worry that you don't have enough 'long-tail' keywords" (Google, July 10, 2026). Relevance means your page answers the question being asked.

Stage 4: whether the model uses and cites your page

Being retrieved does not mean being cited, and being cited does not mean being used. OpenAI's API documentation says "The number of sources is often greater than the number of citations", and in a controlled single-document test on one small model (Llama-3.1-8B), amplifying a few attention heads and MLP layers recovered over 90% of missed citations without changing the source, while gains in multi-document tests were small (arXiv:2606.28358). The full mechanics, and why citation counts from different engines cannot be added up, are in our guide to LLM citations.

What you control here is narrow: whether the facts on the pages a model reads are correct and agree with each other. Rewriting pages to court citations does not help. C-SEO Bench found most such methods "not only largely ineffective but also frequently have a negative impact" (arXiv:2506.11097), and the survey warns "citation-oriented rewrites can impair retrieval."

Brand prominence: the variable no study controls for

Citations concentrate on a few big sources. In AI Search Arena conversations from March to May 2025, the top 20 news outlets took 67.3% of OpenAI models' news citations, 31.9% of Google models' and 28.5% of Perplexity models' (arXiv:2507.05301). The engines differ, but all three concentrate; the study covers news citations only.

That is an association with size, not a lever. Third-party "authority" scores are built from backlinks and traffic, so they measure the same size they are supposed to control for. Any benchmark that compares a startup with a household name is measuring brand size with a GEO label on it.

How to measure LLM brand visibility without fooling yourself

• Keep platforms separate. Google says even AI Overviews and AI Mode "may use different models and techniques"; ChatGPT and Perplexity differ more.
• Record whether each answer searched. Citations are the visible sign; their absence suggests a memory answer.
• Repeat every question. The survey reports "substantial run-to-run variability" in commercial audits.
• Score mention, citation and accuracy separately. Being named with the wrong price is not a win.
• Never report a rank. No engine exposes one, and there is no ground truth to check it against.

For transparency, here is how 99Visibility's multi-platform audit reads each engine. ChatGPT and Claude are queried through their APIs without web search (stage one, memory); Perplexity with web search on; Gemini with Google Search grounding, falling back to no grounding if grounding fails; Google AI Overviews from the live results page, because no API exists.

The 0 to 100 score is our model, not an industry measurement: Mention 40%, Accuracy 30%, Sentiment 15% and Citation 15%, multiplied by platform coverage (0.2 + 0.8 × coverage), weighted ChatGPT 36%, Google AI Overviews 18%, Perplexity 18%, Google AI Mode 10%, Gemini 9% and Claude 9%. A brand no platform mentions scores 0. Our guide to understanding visibility scores covers the reasoning.

Five checks for your brand this week

1. Write down your facts, then ask. Founding year, headquarters, CEO, pricing, main features. Ask each platform what your brand is and costs, and mark every wrong answer and whether it searched.
2. Resolve robots.txt per agent. Allow each vendor's search crawler (OAI-SearchBot, Claude-SearchBot, PerplexityBot, Googlebot, Meta-WebIndexer) and decide training crawlers separately.
3. Test the firewall. Request a key page with each crawler's user-agent string and confirm a 200, then check your CDN logs for the real bots.
4. View source on your key pages. If prices and product names are missing from the raw HTML, crawlers that do not run JavaScript never saw them.
5. Look for suppression. noindex, nosnippet, max-snippet:0, data-nosnippet, and Google Search Console's Search generative AI control.

The platform-specific versions of these checks are in our guides on how to rank in ChatGPT, Perplexity SEO and how to rank in AI Overviews.

Frequently asked questions

What is LLM brand visibility?

It is whether AI models mention your brand when people ask about your category, whether they link to you, and whether what they say is accurate. It differs by platform and by whether the model searched the web for that answer. It is not a rank: AI answers have no positions.

What really drives LLM visibility?

For answers from memory, what the model learned before its training cutoff, which you cannot change quickly. For answers that search, the documented drivers are crawler access and topical relevance to the question; brand size is strongly associated with citation but is not a lever. No markup, phrasing or formatting tactic has shown a stable effect on whether you are found.

How do I get AI visibility?

Make sure each AI vendor's search crawler is allowed in robots.txt and let through by your firewall, put your key facts in the page's HTML, and remove accidental snippet suppression. Then fix contradictions in your own published facts. That covers everything a publisher controls.

Why do ChatGPT and Perplexity say different things about my brand?

They often answer in different modes: Perplexity is built around search, while ChatGPT may answer from memory with a fixed cutoff. When both search, they use different indexes, rewrite the question differently and cite in different units. Treat each platform as its own measurement.

Can you track LLM visibility accurately?

You can track whether you are mentioned, cited and described correctly, if you repeat each question and record whether the answer searched. You cannot see the queries consumer apps actually ran; the Gemini, OpenAI and Perplexity APIs return them for your own calls, and Bing shows a sample for Copilot. No engine exposes a rank.

To see what six AI platforms say about your brand, which facts are wrong, and which crawlers your site turns away, run a free 99Visibility audit.