What is LLM visibility?
LLM visibility is how often and how favourably large language models mention your brand when users ask questions in your category. It is measured by running a fixed set of prompts across assistants and recording whether you are named, which competitors appear instead, and which sources the model cited to build its answer.
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Why does llm visibility matter for your brand?
LLM visibility is the closest thing AI search has to a rank report, but it behaves differently: there is no position one, only cited or not cited. Outputs also vary by phrasing and session, so a single check proves nothing. The signal is the trend across a consistent prompt set over time.
What does it cost to ignore it?
Without a tracked baseline you cannot tell whether AI search is sending you nothing because you are invisible or because nobody is asking — two problems with completely different fixes.
Which engine fixes this?
LLM Visibility is addressed inside The Predictability Engine.
See what The Predictability Engine includesCommon questions
How is LLM visibility measured?
Pick the prompts a real buyer would type, run them across ChatGPT, Perplexity, and Google AI Overviews on a fixed schedule, and log three things each time: whether you were named, who was named instead, and which URLs were cited. The count of mentions across that prompt set, tracked over months, is the metric — not any single answer.
Why do I get a different answer every time I ask?
Because model outputs are probabilistic and change with phrasing, session history, and model version. The same question asked twice can name different companies. This is why one screenshot is not evidence in either direction, and why any tool or agency reporting a single check as proof is misreading its own data.
Sources
Ryan Goering
CEO & Founder, BaaDigi
U.S. military veteran and digital marketing strategist who built BaaDigi to help contractors generate predictable leads and revenue. 15+ years in SEO, PPC, and AI-powered marketing automation.