AI Visibility Score: How to Measure and Benchmark Your Performance
An AI visibility score is a composite metric quantifying how visible, prominent, and positively represented your brand is across AI-generated responses. It combines mention frequency, sentiment, accuracy, position, and share of voice into a single actionable number.
What Is an AI Visibility Score?
The score aggregates several sub-metrics into a single number, typically on a 0-100 scale. It answers: how well is my brand represented across AI systems? Citerna calculates this across all 11 models.
Components of the Score
Mention frequency measures how often your brand appears. Mention quality examines position and prominence. Sentiment evaluates positive vs negative framing. Accuracy checks factual correctness of AI statements. Share of voice provides competitive context.
How to Use Your Score
Track over time to measure optimization impact. Compare against competitors. Drill into sub-metrics for specific improvement areas. Use score changes to justify AI visibility investment.
Improving Your Score
Focus on weakest sub-metrics first. If sentiment is low, address negative characterizations. If frequency is low, create content for missing prompts. If accuracy is poor, ensure correct structured information.
Industry Benchmarks
Category leaders typically score 70-90. Strong performers: 50-70. Brands starting: 20-40. The trajectory matters more than the absolute number.
Frequently Asked Questions
What is an AI visibility score?
A composite metric combining mention frequency, sentiment, accuracy, position, and share of voice into a single number measuring AI presence.
How is the score calculated?
It aggregates sub-metrics across multiple AI models, weighted by impact on brand perception. Citerna scores on a 0-100 scale.
What is a good AI visibility score?
Category leaders: 70-90. Strong performers: 50-70. Starting out: 20-40.
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