Entity Consistency Score

Extended definition

Entity Consistency Score measures uniformity in how your brand entity appears across your content ecosystem: consistent company name (not varying between 'Company Inc.', 'Company', 'Company Corp'), consistent product names (not switching between 'Product X' and 'X Platform'), consistent descriptions (same category language), consistent formatting (logo, URLs, structured data), and consistent relationship declarations. High consistency means AI encounters the same entity signals everywhere; low consistency creates confusion as AI can't determine if different mentions refer to the same entity. Score calculation examines mention variance, naming patterns, description consistency, and schema uniformity.

Why this matters for AI search visibility

Inconsistent entity representation fragments your authority across multiple perceived entities. AI might think 'Company X' and 'X Corp' are different companies, splitting citation credit. Inconsistent product naming causes AI to treat variations as different products. Inconsistent descriptions confuse category classification. Entity Consistency directly impacts recognition accuracy and citation consolidation. For growing companies, consistency often degrades as different teams create content with varying conventions. Consistency audits reveal fragmentation that's invisible to humans but devastating to AI understanding. High consistency scores enable reliable entity extraction and consolidated authority.

Practical examples

• Consistency audit reveals brand mentioned 14 different ways across content, fragmenting entity recognition and reducing citations by estimated 67%
• Standardizing entity mentions to single consistent format increases entity recognition from 54% to 93% and consolidates split authority
• Entity consistency improvement from score of 31 to 94 correlates with 3.8x increase in consolidated citation rate