Entity Analysis
Understand how AI models perceive your brand as an entity — attributes, relationships, confusions, and clarity scoring.
Overview
Entity Analysis examines how AI models perceive your brand as a distinct entity. It extracts key facts (attributes) that AI models associate with your brand, identifies related entities, detects confusion with other brands, and produces a Clarity Score measuring how accurately AI models describe you.
This feature works on your existing snapshot data — no additional configuration is required beyond having captured snapshots.
Key Metrics
Entity Clarity Score (0–100)
The Clarity Score measures how accurately and consistently AI models describe your brand. It factors in:
- Attribute accuracy — Are the facts AI states about you correct?
- Relationship quality — Are entity associations relevant?
- Confusion count — How often is your brand mixed up with another?
- Data volume — More snapshots = higher confidence.
| Score Range | Label | Interpretation |
|---|---|---|
| 80–100 | Excellent | AI models describe your brand accurately and consistently. |
| 60–79 | Good | Most attributes are correct; minor gaps exist. |
| 40–59 | Fair | Some inaccuracies or confusion detected. |
| 20–39 | Poor | Significant misrepresentation by AI models. |
| 0–19 | Very Poor | AI models frequently misidentify or confuse your brand. |
Attributes Found
The system extracts factual claims AI models make about your brand:
- Identity — What the brand "is" (e.g., "Apple is a technology company")
- Founded — Year established
- Headquarters — Location
- Leadership — CEO, founder names
- Specialization — Core focus areas
Each attribute is marked as Accurate, Inaccurate, or Unverified based on comparison with your Brand Facts.
Related Entities
Other brands, companies, or concepts that AI models frequently mention alongside your brand. Each relationship shows:
- The entity name and relationship type (competitor, partner, parent company, etc.)
- Mention count across snapshots
- Sentiment of the association (positive, neutral, negative)
Entity Confusions
Cases where AI models mix up your brand with another entity. Detected from phrases like:
- "not to be confused with…"
- "sometimes confused with…"
- "unlike [brand], [your brand]…"
How to Use
- Navigate to Entity Analysis in the sidebar (under Analysis).
- Review the summary cards for a quick health check.
- Check the Attribute Details table — are the facts correct?
- Address any Entity Confusions by creating distinct, differentiating content.
- Add Brand Facts in Settings to enable accuracy verification.
Improving Your Clarity Score
- Add Brand Facts — Go to Settings and add verified facts about your company (founding year, headquarters, leadership, etc.). This enables the accuracy verification system.
- Publish clear factual content — Ensure your website clearly states key company facts.
- Use structured data — Organization schema, FAQ schema, and HowTo schema help AI models understand your brand.
- Address confusion — If AI confuses your brand with another, create content that explicitly differentiates you.
- Capture more snapshots — More data means higher confidence in the analysis.
Plan Requirements
Entity Analysis requires the Advanced AI Insights feature, available on Starter plans and above.