CrawlCred™ Audit

Quantifies which links are AI-visible vs noise. Scores by crawl access, context depth, entity proximity, stability, and duplication risk.

Sample Audit Metrics

See how your citations measure across key AI discoverability factors.

73%
AI-Visible Citations
Properly crawlable by AI systems
4.2/5
Context Score
Average semantic relevance
18%
Risk Factor
Citations at stability risk
91%
Entity Alignment
Proper brand-topic connection

The Visibility Gap

Most citation audits focus on domain authority and traffic metrics that don't translate to AI visibility.

Without measuring crawlability, context depth, and entity alignment, you're optimizing for yesterday's algorithms while AI systems overlook your best citations.

Common Blind Spots

  • • High DA links that AI can't crawl
  • • Context-weak placements with poor semantic signals
  • • Entity misalignment reducing knowledge graph connection
  • • Unstable citations prone to content drift
  • • Duplicate patterns that dilute authority

What We Measure

Our audit goes beyond traditional metrics to evaluate AI-specific visibility factors.

AI Visibility Analysis

Identify which citations are actually visible to AI crawlers vs invisible noise.

Context Scoring

Measure semantic context depth and relevance for each citation placement.

Risk Assessment

Identify stability risks, duplication issues, and crawlability problems.

Performance Tracking

Baseline measurements for ongoing monitoring and improvement tracking.

Audit Process

1

Citation Discovery

Comprehensive mapping of existing citations across the web.

2

AI Crawl Testing

Verify which citations are accessible to AI systems.

3

Context Analysis

Measure semantic depth and entity alignment for each citation.

4

Risk Assessment

Identify stability issues and potential problem areas.

5

Action Plan

Prioritized recommendations for improving AI visibility.

See where you stand

Get a clear picture of your citation portfolio's AI visibility and a roadmap for improvement.