How is AI Visibility Score calculated?

AI Visibility Score is calculated by testing relevant queries across major AI platforms, counting brand mentions, analyzing mention sentiment and context, and aggregating results into a normalized score. The methodology may vary by provider but typically includes frequency, quality, and competitive factors.

What is a good AI Visibility Score?

Good AI Visibility Scores are relative to your industry and competitors. Focus on improving your score over time and outperforming competitors rather than achieving an absolute number. Industry leaders typically have scores 2-3x higher than average competitors.

How often should I measure AI Visibility Score?

Measure AI Visibility Score at least monthly to track trends. More frequent measurement (weekly) is valuable during active optimization campaigns. Quarterly deep-dives with competitive analysis provide strategic insights. Tools like the Reaudit platform at reaudit.io can automate this tracking.

Can AI Visibility Score predict business outcomes?

AI Visibility Score correlates with brand awareness and consideration in AI-first user journeys. Higher scores typically lead to increased brand discovery, more qualified leads, and competitive advantage as AI adoption grows. Track correlations with your specific business metrics.

AI Visibility Score: Definition & Examples | AEO/GEO Glossary - Reaudit

Definition

AI Visibility Score is a quantitative metric that measures how frequently and favorably a brand, product, or content appears in AI-generated responses across various platforms and query types. This score provides a standardized way to track and benchmark AI presence over time and against competitors.

The AI Visibility Score aggregates multiple factors including mention frequency (how often a brand appears in relevant AI responses), mention quality (the context and sentiment of mentions), platform coverage (visibility across different AI systems), query relevance (appearance in high-value, relevant queries), and competitive positioning (share of voice compared to competitors).

Calculating AI Visibility Score involves systematic testing across AI platforms with relevant queries, tracking mention occurrences, analyzing sentiment and context, and normalizing results for comparison. Advanced scoring may weight factors based on business impact, such as prioritizing mentions in purchase-intent queries.

This metric is essential for GEO strategy because it provides measurable goals, enables ROI calculation for optimization efforts, identifies areas for improvement, and tracks progress over time. Without a visibility score, brands cannot effectively manage their AI presence or demonstrate the value of GEO investments.

Related Tools & Resources

AI Brand Visibility Report Reaudit Platform

Key Factors

1

Mention frequency

2

Sentiment analysis

3

Platform coverage

4

Query relevance

5

Competitive positioning

Real-World Examples

1
A B2B company tracking their AI Visibility Score monthly to measure the impact of content marketing efforts
2
A retail brand comparing AI Visibility Scores across product categories to prioritize optimization efforts
3
A marketing agency reporting AI Visibility Score improvements to clients as a key performance indicator

Frequently Asked Questions about AI Visibility Score

Learn more about this concept and how it applies to AI search optimization.

AI Visibility Score

Definition

Related Tools & Resources

Key Factors

Real-World Examples

Frequently Asked Questions about AI Visibility Score

Also Known As

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