Revenue shifted. Costs spiked. Conversions dropped. Your data holds the answer—but the causes are hidden, overlapping, and impossible to untangle manually.
FactorPrism® uses AI to automatically decompose your data and reveal the underlying drivers of every change. See exactly which factors caused what—in seconds, not weeks. Running natively in Snowflake, your data never leaves your secure environment.
Behind every metric shift are hidden causes: seasonal patterns, market trends, operational changes, competitive moves—all overlapping and compounding in ways that are impossible to untangle manually. These underlying drivers determine your performance, but they stay invisible in traditional analysis.
FactorPrism® uses AI to automatically decompose your data into its component drivers. Our algorithms separate overlapping effects, isolate each factor's true contribution, and quantify exactly how much each one impacts your results. What would take analysts months to hypothesize and test, FactorPrism® discovers in minutes.
The result? You finally see the causes behind your performance—not just what changed, but exactly which underlying factors drove that change and by how much.
All the power of advanced causal analysis with the security and governance your enterprise demands.
Stop guessing. Automatically identify the specific segments driving changes in your metrics.
Analysis runs entirely in your Snowflake warehouse. Your data never leaves your environment, with full governance controls.
See exactly how much each driver contributed with intuitive visualizations and AI-powered insights.
From installation to insights in under 10 minutes.
Grant FactorPrism® read-only access to your Snowflake tables. We only need SELECT permissions—your data stays exactly where it is.
Define your dimensions: Region, Product, Customer Type, Time Period—whatever segments matter to your business.
Run your analysis and get AI-powered insights showing exactly which segments are driving your performance up or down.
Per quarter on analysis
Than traditional methods
Of analyst headcount annually
In our NYC case study
When we analyzed NYC's 311 service data, the headline looked simple: 11% growth in complaints. But FactorPrism® automatically decomposed this into the real story:
These insights would take months of manual analysis to uncover. FactorPrism® found them automatically.
See How We Did ItOne number (11% growth) became dozens of actionable insights:
"Complaints are up 11%"
"Overall growth masks a 25% drop in housing issues, seasonal water system stress, and infrastructure failures in specific years"
Revenue grew 12%. Traditional analysis allocated it all at the regional level. FactorPrism® found the right hierarchy: half was a company-wide lift, while Northeast was hiding a -3% drag behind that baseline.
Read case studyTraditional BI showed "Jewelry +22%" and "South +24%" as separate dimensions. FactorPrism® found the right level: South + Jewelry intersection drove 9% of the 18% growth—the real driver was one specific combination.
Read case studyLet AI decompose your performance into its underlying causes. FactorPrism® runs natively in Snowflake—your data stays secure while you finally see what's really driving your performance.
