What does this AI visibility score measure?
It summarizes observed answers from a defined prompt test. The composite weights brand visibility at 50%, prominence at 20%, claimed-domain citations at 20%, and factual accuracy at 10%.
An AI visibility score summarizes a defined prompt test. Calculate one from real answer counts while keeping visibility, prominence, citations, accuracy, and coverage separate.
AI visibility score definition
An AI visibility score summarizes how a target brand performed in a defined set of AI-generated answers. It is not a permanent rank, a property of the domain, or a universal grade. Its meaning depends on the questions, providers, market, date, grounding rules, and formula used to create it.
The calculator below weights discovery visibility at 50%, prominence at 20%, claimed-domain citations at 20%, and factual accuracy at 10%. Coverage stays separate so failed collection cannot masquerade as low brand visibility. See how those metrics map to AEO and GEO outcomes.
Observed-answer inputs
Answers successfully collected with the required grounding.
Count the brand only when it appears in the answer itself.
Answers where the brand leads or appears in the primary shortlist.
Eligible answers linking to the brand's canonical domain.
Mentioning answers with materially correct positioning and facts.
Transparent composite
Composite = 50% visibility + 20% prominence + 20% claimed-domain citation rate + 10% factual accuracy. Keep the components visible; the composite alone cannot explain what changed.
mentions ÷ eligible answers
prominent ÷ mentioning answers
claimed-domain citations ÷ eligible answers
accurate ÷ mentioning answers
Interpretation guardrail
The same brand can score differently when the question set, providers, locale, web-search behavior, date, or eligibility rules change. Save those conditions beside every score.
Compare reruns only against the same frozen benchmark. Read the component rates before acting: a citation problem requires a different response from an accuracy or discovery problem.
Need the underlying answer evidence rather than manual counts? The AI search visibility tool runs 25 frozen buyer questions across four grounded providers and preserves every eligible answer, source, and failure.
Contextual next steps
Use the next resource that matches the decision at hand: define the program, inspect the method, or collect a comparable cross-provider baseline.
Run a frozen 25-question benchmark across four providers and inspect the underlying answer evidence.
02Map answer selection, brand understanding, SEO, and cross-model measurement to the right program.
03Preserve provider conditions, answers, citations, competitors, and comparable reruns.
Common questions
It summarizes observed answers from a defined prompt test. The composite weights brand visibility at 50%, prominence at 20%, claimed-domain citations at 20%, and factual accuracy at 10%.
No. Website readiness and observed answer visibility are different measurements. Enter counts from real, time-stamped AI answers rather than inferring visibility from schema, word count, or other proxies.
An eligible answer completed under the defined protocol and met any required grounding or source conditions. Failures and unsupported runs belong in coverage, not silently in the miss denominator.
Only when the tools use the same questions, providers, collection conditions, eligibility rules, and formula. Otherwise similar-looking scores can measure materially different things.
Apply this resource
Preserve the questions, conditions, answers, citations, and failures so the next decision rests on inspectable evidence.