What is LLM visibility?
LLM visibility is how readily a brand shows up when people ask large language models questions in its category. It includes named mentions, linked citations, and the competitors that appear instead. It is an observation across prompts and engines, not a single score those engines publish.
Why it matters for AI visibility
A homepage can rank in classic search and still be absent when a buyer asks an assistant for a shortlist. LLM visibility is the name for that gap. Teams judge it by asking the same buyer questions in ChatGPT, Gemini, Perplexity, Claude and Google’s AI features, then logging who is named and which URLs are cited. Repeating the check matters because one run can differ from the next. A useful report separates engines, separates mentions from citations, and keeps the prompt list stable so a change in the list is not mistaken for a change in visibility. Tools can summarize that log. They do not replace reading the answer and the sources underneath it.
Example
A team tracks twelve buyer prompts each month. In one month the brand is named in four prompts and cited in one. The following month it is named in four and cited in three, on the same prompts. That shift is an LLM visibility change. It is not, by itself, proof of which page caused it.
Related terms
LLM visibility is the broad outcome. An AI citation is one linked source inside an answer. Citation share and share of voice describe your portion of citations or mentions relative to others. Report those metrics separately so a mention is not counted as a citation.