survey and data collection firms often preclude delivery of anything but high level summarizations and descriptive statistics with newly collected data.
QuickHit™ is a causal analytics solution designed to provide rapid causal analysis for firms seeking to provide additional interpretive value under tight time constraints. QuickHit™ augments typical descriptive findings and statistics with a rapid snapshot of the causal drivers behind those results. QuickHit™ also supports execution of individual tests should further analysis of data siubsets be desired,
Here's what QuickHit™ provides:
Missing Data Treatment - supports both data imputation and recoding
Single Click Causal Analysis - upon
selection of dependent and independent
Bayesian Network Diagram - directed acyclic graphs charting conditional dependencies between the dependent measure and potential causal drivers
Variable Importance Plot - for all variables included in the Bayesian analysis based on random forest techniques
Regression Models - to determine which independent variables are the statistically significant drivers of the dependent measure. Output includes added variable plots, all subsets regression, and regression diagnostic plots.
Classification Tree - based on random forest machine learning procedures
Selective Procedures - all preceding analyses can be individually invoked on smaller subsets of variables
To Predict What People Will Do
Listen to What They Say
But Act On the Motivations Behind What They Say
Variable Importance Plot
Are you in the opinion poll and survey business? Do you deliver the descriptive results from five or more surveys to clients each day? The rapid performance pressures on