Using Regression based Control Limits and Probability Mixture Models for Monitoring Customer Behavior

Abstract

In order to achieve the maximum flexibility in adaptation to ever changing customer's expectations in customer relationship management, appropriate measures of customer behavior should be continually monitored. To this end, control charts adjusted for buyer's/visitor's prior intention to repurchase or visit again are suitable means taking into account the heterogeneity across customers. In the case of a subscription-based service provider, this paper discusses three types of adjusted control charts considering grouped data on attribute usage measures are available at each subscription period. With appreciating the characterizing effect of customer's overall satisfaction on his future behavior, regression based models and probability mixture models are used to account for heterogeneity in customers' mean usage rate. Besides adjusted Shewhart and CUSUM control charts for Bernoulli and Poisson distributed usage indicators, the likelihood ratio test based on mixture probability models are investigated in term of detect ability of the shifts in usage behavior through a comparative simulation study.