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. QuickHitalso 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

    variables, generates:

    • 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
    Bayesian Network
    Classification Tree
    Survey Responses

    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