Glossary

What is AI Visibility Score?

A composite metric summarizing brand presence across AI assistants — mention rate, citation rate, position, and sentiment in one trackable number.

Definition

An AI visibility score is a composite metric condensing brand presence in AI answers into one trackable number — typically combining mention rate (how often you appear for tracked prompts), citation rate, average position among named brands, and sentiment, across assistants and time.

It's the AI-era analog of an SEO visibility index, built on prompt-tracking samples rather than rank positions.

Why it matters

Executives need one number with a trendline; practitioners need the decomposition. A good score supplies both: the headline tracks program health, while its components diagnose cause — mentions down because ChatGPT changed sources? Citations up after the data-study launch? Because LLM answers vary run to run, scores built on repeated sampling are meaningful where single-query spot-checks are noise. Treat any tool's absolute score as its own scale; the trend and competitor gap are the signal.

Frequently asked

What makes a visibility score trustworthy?

Transparent methodology: which prompts, which assistants, how many samples, how components weigh. Distrust scores that won't show their inputs — variance across LLM runs makes undisclosed methodology unfalsifiable.

How often should the score update?

Weekly sampling is a practical floor for trend detection; daily for competitive categories. What matters is consistency — same prompts, same method — so movement reflects the market, not the measurement.

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