AI Visibility
measured32/100
Emerging · in Data & Analytics
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals9/100
Weak fundamentals
Avg Prompt Score
52
across 565 prompts
AI Share of Voice
52%
across 565 prompts
Critical Issues
4
critical + high
Shortlist Position
2/80
Not Visible · Marketing Analytics Discovery
How AI Visibility breaks down
in Data & Analytics
Composite = 60% coverage + 40% engine breadth, 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.
Categories Quant is visible in
2Your visibility gap
Quant surfaces in 2/80 Marketing Analytics discovery prompts. Claim this profile to see which 78 prompts you're missing and how to win them.
Executive summary
Quant Retail is a B2B SaaS with strong third-party review visibility (G2 and Gartner Peer Insights exist) and a publicly crawlable pricing page with explicit starting prices. The biggest AI-citation risk is category mismatch: the site is optimized for retail space/planogram analytics, so it is missing from high-intent marketing-analytics buyer queries (e.g., “best marketing analytics software for B2B companies” and “how to improve customer insights with marketing analytics”). The single highest-ROI fix is to publish evaluation-stage, marketing-analytics-specific pages (what it is, who it’s for, integrations, and pricing/ROI) that map Quant’s retail analytics capabilities to marketing analytics use cases, then ensure those pages are crawlable and schema-marked for AI extraction.
Based on audit of quantretail.com · May 7, 2026