Definition
An AI visibility score is a composite metric that summarizes how visible a brand is across AI answers. Tools typically blend several inputs, such as how often the brand is mentioned, how often its pages are cited, where it appears in the answer and whether the description is positive.
For example, Aarvi Skin's score might rise from one month to the next because it was cited more often in Perplexity, even though its mention rate in ChatGPT stayed flat. The score shows that something changed, but only the underlying parts explain what changed and why.
Why it matters
A single number is useful for tracking direction over time and for giving leadership a quick summary. The risk is treating it as the whole story. Each tool weights its inputs differently, so two tools can give different scores for the same brand, and a score can rise while an important signal falls. Use the score to notice change, then read the components and answers underneath to understand the cause.
What to do
- Ask your tool which signals the score includes and how each one is weighted.
- Review the component metrics whenever the score moves, before reporting the change.
- Compare scores only within the same tool, question set and time period.
Common questions
Why do different tools give different AI visibility scores?
Each tool chooses its own inputs, weights, question sets and sampling schedule. One may emphasize citations while another weights mentions or sentiment more heavily. These choices change the result, so scores from different tools are not directly comparable. Compare trends within one tool instead.
Should an AI visibility score be a marketing KPI?
It can work as a summary indicator, but pair it with the components that matter for your goals, such as citation rate for key pages or mention rate on high-intent questions. That way a change in the score always links back to something the team can investigate.