AI Visibility
measured70/100
Frequently Cited · in Data Warehouse
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals63/100
Some gaps
Avg Prompt Score
31
across 773 prompts
AI Share of Voice
30%
across 753 prompts
Critical Issues
4
critical + high
How AI Visibility breaks down
in Data Warehouse
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.
Categories Databricks is visible in
3Executive summary
Databricks is highly likely to be cited by AI engines for category and evaluation queries because it has strong third-party authority (e.g., 657 G2 reviews at 4.6★) and an enterprise review footprint (Gartner Peer Insights page exists). The single highest-ROI fix is to add/ensure first-party, crawlable evaluation content that directly targets the comparison and pricing prompts (especially "How does Databricks compare to Snowflake?" and "How much does Databricks cost?") with SSR + structured Q&A blocks so AI engines can cite Databricks pages instead of only third parties.
Based on audit of databricks.com · Apr 2, 2026