The LLM Visibility Score™ is a proprietary diagnostic framework that measures how visible a business is inside AI-generated answers, citations, snapshots, and recommendations. It evaluates how well a brand is understood, trusted, and surfaced by major AI systems, including ChatGPT, Claude, Gemini, and Perplexity.
This score provides a clear, structured way to assess your authority inside LLM ecosystems.
Why the LLM Visibility Score™ Matters
As AI-generated answers replace traditional search, businesses need a reliable way to benchmark their presence inside these systems. Traditional SEO metrics do not reflect how LLMs interpret or surface information.
The LLM Visibility Score™ measures visibility across:
- Entity clarity
- Semantic structure
- Topic authority
- Content extractability
- Citation likelihood
- Snapshot appearances
- Retrieval alignment
It reveals whether a business is discoverable—or invisible—in AI search environments.
How the LLM Visibility Score™ Works
The score evaluates visibility across seven core factors:
1. Entity Recognition
How clearly AI systems understand your identity and domain.
2. Semantic Consistency
Whether your terminology and topic structure are aligned.
3. Authority Signals
Strength of structured, evidence-based content.
4. Topic Coverage
Depth and breadth across key clusters.
5. Extractable Formats
Use of definitions, lists, frameworks, and Q&A.
6. Retrieval Alignment
How well your content matches model retrieval patterns.
7. Citation Behavior
How often AI systems reference your content type.
These factors combine to create a reliable measure of AI visibility.
Using the LLM Visibility Score™
Businesses use the score to:
- Identify visibility gaps
- Prioritize optimizations
- Benchmark AI authority
- Track improvements over time
- Understand their “AI search footprint”
It is the foundation of our diagnostic and engagement process.
Related Pillars
- The 7-Layer LLM Ranking Stack™
- Source Authority & Trust Signals
- LLM Citation Signals
- Entity Optimization for AI Search
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