Reference
AI Clarity Index Glossary
Definitions for every metric and key term used in the AI Clarity Index methodology.
ACI Score
The composite AI Clarity Index score, ranging from 0 to 100, that represents a business’s overall AI visibility. Calculated as a weighted combination of six metrics: ECS (20%), SAS (20%), NCS (15%), CMV (15%), CCI (15%), DRI (15%).
Entity Clarity Score (ECS)
Measures whether AI correctly identifies a business’s name, location, and core identity. A low ECS means AI confuses the business with another entity or misidentifies fundamental attributes.
Source Alignment Score (SAS)
Measures whether AI-generated claims about a business’s services, history, and offerings are factually accurate when compared against verified sources.
Narrative Consistency Score (NCS)
Measures whether a single AI model tells a consistent story about a business across different query types (direct, category, recommendation, comparison, authority).
Cross-Model Variance (CMV)
Measures the gap between the most and least accurate AI models when describing a business. High variance means models significantly disagree, creating an unpredictable customer experience.
Consensus Confidence Index (CCI)
Measures the confidence and correctness of consensus when multiple AI models agree on claims about a business. High CCI means models agree and are correct; low CCI means models agree but are wrong.
Drift Risk Indicator (DRI)
Identifies signals that a business’s AI visibility may degrade over time — such as reliance on a single outdated source, rapidly changing competitive landscape, or thin content signals.
AI Visibility
The degree to which AI language models accurately represent a business in response to user queries. Encompasses recognition (does AI know you exist?), accuracy (does it get the facts right?), and recommendation (does it suggest you?).
Entity Confusion
When an AI model confuses one business with another, typically due to similar names, shared locations, or overlapping service categories. One of the most common and damaging AI visibility failures.
Answer Engine Optimization (AEO)
The practice of optimizing a business’s digital presence to improve how AI language models represent and recommend it. Distinct from SEO, which targets search engine ranking algorithms.
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