The 6-metric framework
VectorGap measures AI perception across six distinct dimensions. Each captures a different aspect of how AI represents your brand.
1. Accuracy (0-100)
What it measures: Whether AI states factually correct information about your brand.
How it's calculated: We compare specific claims in AI responses against your knowledge base. Each claim is marked as accurate, inaccurate, or unverifiable.
What affects it: Outdated information, hallucinations, entity confusion.
How to improve: Build a comprehensive knowledge base. Create structured content with clear, verifiable facts.
2. Sentiment (0-100)
What it measures: The emotional tone AI uses when discussing your brand.
Score interpretation: 0-40 (predominantly negative), 41-60 (neutral/mixed), 61-80 (positive), 81-100 (very positive).
What affects it: Customer reviews, press coverage, competitor comparison pages.
3. Visibility (0-100)
What it measures: How prominently you appear in AI responses to relevant queries.
How it's calculated: First mention (100 points), second mention (80 points), third mention (60 points), lower or not mentioned (decreasing points).
What affects it: Brand authority, content volume, structured data, citation frequency.
4. Coverage (0-100)
What it measures: Whether AI mentions your key features, differentiators, and use cases.
Example: If your knowledge base lists 10 key features and AI mentions 6, your coverage is 60%.
5. Credibility (0-100)
What it measures: How authoritative AI sounds when discussing your brand.
Factors: Does AI cite sources? Use confident vs. hedging language? Present you as established or unknown?
6. Recommendation (0-100)
What it measures: Whether AI actively recommends your product to users.
The difference: Mention says "Company X exists" while Recommendation says "Company X is a good choice for [use case]".
This metric correlates most directly with AI-driven conversions.