AI Visibility
measured35/100
Emerging · in Applicant Tracking
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals66/100
Solid fundamentals
Avg Prompt Score
87
across 42 prompts
AI Share of Voice
100%
across 26 prompts
Critical Issues
2
critical + high
How AI Visibility breaks down
in Applicant Tracking
Composite = 50% coverage + 30% engine breadth + 20% position, measured in the brand's strongest category. Position and citation depth join the score once the aggregation pipeline captures them. This is the measured Visibility score — separate from AEO Readiness, which scores fundamentals.
Per-stage performance
Cited rate · share of voice · engine consensus · sentiment, broken out by buyer-journey stage. Sentiment is the net positive−negative skew across engines that cited the brand at this stage.
Executive summary
CodeSignal is highly likely to be cited by AI engines for evaluation-stage queries because it has strong third-party review presence (1,408 G2 reviews) and a publicly crawlable pricing page with explicit tiers and prices. The single highest-ROI fix is to add/verify B2B-structured evaluation markup (SoftwareApplication + FAQPage targeting pricing/integrations/vs queries) and ensure it’s present on the key SSR pages so AI engines can reliably extract “what it is / who it’s for / how much it costs” answers.
Based on audit of codesignal.com · Aug 29, 2026