How large language models decide which brands to mention and what you can do to improve your chances.
What is LLM visibility?
LLM visibility is the degree to which your brand appears in answers generated by large language models (LLMs) like ChatGPT, Claude, Gemini, and Perplexity. It is a measure of how present and credible your brand is in the sources that LLMs draw from when constructing responses — and it is increasingly important as buyers use these systems to research vendors and services.
Large language models generate answers by synthesising information from their training data and, in many cases, from real-time web retrieval. The brands that appear in those answers are the brands that have established a presence in the sources LLMs trust: established media outlets, industry publications, research databases, association directories, and well-cited web content.
LLM visibility is distinct from general brand visibility. A brand can be well-known to its existing customers and still have poor LLM visibility — because the brand's expertise has not been documented in the sources that LLMs access. Conversely, a relatively small brand with a strong publication record and consistent third-party citations can have strong LLM visibility in its niche.
The gap between LLM visibility and traditional brand awareness is where Authority Building Events create the most value. An event that generates a media article, 5 speaker LinkedIn posts, an event recap on an industry blog, and a citation in a journalist's research notes creates 8–10 new LLM citation points from a single production. Over 12–24 months of events, those citations accumulate into a documented presence that LLMs can reliably surface.
For B2B brands, LLM visibility matters because the research journey for high-value purchases increasingly starts with an AI query. A buyer who asks an LLM "which firms run industry roundtables for accounting firms in Edmonton?" and gets your brand's name in the response has a higher probability of reaching out than a buyer who finds you through a cold search.
Common questions
The most direct method is manual querying: ask ChatGPT, Perplexity, and similar systems 10–15 questions that your ideal buyers might ask, and record which brands are mentioned. This gives you a benchmark. Repeat quarterly to track changes. Some dedicated LLM monitoring tools are emerging, but manual querying remains the most accessible measurement approach.
Improve your LLM visibility
Tell us the date, the headcount, and what you are trying to accomplish. We will come back with an honest assessment.