2014 BayesiaLab User Conference Presentations
Using Bayesian Networks to Model Key Drivers
Mick McWilliams, Ph.D.
Senior Vice President, Marketing Science, Lieberman Research Worldwide
Recorded on September 24, 2014, at UCLA.
Bayesian network modeling offers a number of advantages as compared non-Bayesian multivariate analytical techniques that have traditionally dominated advanced analytics in marketing research. Bayesian modeling offers some particularly compelling advantages in the area of "drivers analysis;" That is, when the need is to determine which among a set of potential "drivers" can be leveraged to most effectively influence some targeted behavior in the marketplace. This presentation will explain Bayesian network modeling's particular advantages with respect to (1) mitigating problems of multicollinearity, and (2) accounting for the influence of interactive associations between drivers in the analysis.