AI visibility is measured by observing whether, where and how a brand appears across a controlled set of questions and answer systems.
A single screenshot is an observation. A repeated method creates a baseline.
How often the brand is named across the defined question set.
How often an answer points to the brand's site as a source. A citation is not automatically a recommendation.
How often the brand appears relative to the competitors observed across the same test.
Technical readiness may be reviewed alongside these measures, but it is an input, not a visibility outcome.
Platforms, prompts, markets and competitors.
Full answers, cited sources, date and context.
Mentions, roles, citations and description accuracy.
Separate observed evidence from interpretation.
Use the same core test to observe change.
Prompt sets should reflect real customer questions. Repetition captures variance instead of hiding it. Dating and preserving the full answers makes later comparisons reviewable.
Relevant evidence is not being found.
The brand, service or location is misinterpreted.
Important claims lack support.
Another brand has a clearer retrievable trail.
Cited turns controlled prompt testing, citations and competitor patterns into evidence an analyst can review.
Explore the Cited AI Visibility Audit →