Authors: S. Tom Au, Rong Duan, Guangqin Ma and Rensheng Wang
In telecommunications service industry, a group of customers may be targeted for a set of marketing interests, and these interests are usually inter-correlated. For example, churn, up selling and appetency are often considered together, and decisions on how to retain customers, and to promote or to upgrade services are associated. Instead of predicting them separately as univariate models, we propose an adaptive procedure to model multiple responses prediction into correlated multivariate predicting scheme. This adaptive procedure utilizes the correlation structure of the predictors and the responses to enhance the prediction iteratively. This proposed method combines partial least squares (PLS) method and logistic regressions, in which the former is used to extract the mutual information from correlations, while the latter is utilized to refine every single response prediction through auxiliary information from PLS predictions.
Keywords: Correlation, Multivariate predictive modeling