--- language: en title: "Visibility score" description: "A brand presence indicator whose formula depends on the provider. Understand Profound’s denominator and why different scores require explicit methodologies." canonical: "https://tropk.ai/en/resources/glossary/visibility-score" last_modified: "2026-10-12T16:12:18.982Z" --- # Visibility score Reviewed on 2026-10-06. ## What it means A visibility score is an indicator that summarizes a brand’s presence in the responses tracked by a tool. Its meaning depends on the provider’s formula, dataset, and filters. The name alone does not tell you whether the value represents a percentage of responses or a weighted combination of presence, position, and other signals defined by the system. ## Why it matters for marketing Marketing teams use the score to track segments and communicate changes, but they need to know what caused the number to vary. A change in the questions, eligible competitors, or weights can alter the indicator without a corresponding change in the responses. When choosing a tool or consolidating reports, the team should request the methodology and avoid comparing scores just because they share the same scale. ## Example in practice Imagine an agency evaluates one hundred valid responses on a topic: sixty mention a brand, and twenty include its client. Using Profound’s published formula, the Visibility Score would be 20 divided by 60, or approximately 33.3%. Across all one hundred valid responses, presence would be 20%. The agency reports both denominators and explains the difference before presenting the report. ## How to apply or verify In Profound’s documentation consulted in October 2026, the formula is responses with the brand divided by responses that include at least one brand, multiplied by one hundred. Check this filter in the report and preserve the counts, platform, and period. If another provider uses a composite score, request its components, weights, normalization, and version; without these details, note that the methodology remains incomplete. ## Important distinctions A percentage score with a filtered denominator is not equivalent to presence calculated across all valid responses. A composite score should not be called a percentage of responses without methodological support. A ranking orders brands according to an indicator; frequency counts occurrences of the name. None of these values, on its own, measures users reached, buyer preference, or sales attributable to AI. ## Sources and references - [The AI Search Glossary: A definition of 300+ terms]() — Profound - [Profound glossary]() — Profound - [About Answer Engine Insights (AEI)]() — Profound ## Continue a leitura - [Visibility ranking]() - [AI Share of Voice]() - [AI presence rate]() ## About the author [Luiz Gardelin]() Luiz Gardelin is the founder of Tropk.ai and works in GEO/AEO, product vision, strategy, and growth, helping brands understand and improve their presence in AI responses. --- [All pages in Markdown]()