Customer value assessment of pharmaceutical marketing in Taiwan

The purpose of this study is to provide a data mining approach for classifying Taiwanese healthcare institutions based on customer value assessment. Each institution type has developed its own marketing strategy along with relationship management strategies.

Real transaction data from 88 pharmaceutical companies were the study samples. Expert interviews were conducted to analyze industry knowledge. The frequency, money, and contract term (FMC) model was developed to assess and segment the healthcare institutions. ANOVA and the Scheffe post-test were used to explore the test effects of each FMC indicator among the groups. The C5.0 decision tree was then used to generate the behavioral rules of various segmentations. Finally, this study combined the related variables with the purchasing behavioral rules to propose specific strategies for each type of healthcare institution.

A total of 663 health care institutions in Taiwan were divided into four types: loyalist, intellectualist, nitpicking, and churn. The terms frequency (F), money (M) and contract term (C) were all significant indicators for determining the differences among the four customer categories at the 0.01 level of significance. The behavioral rules related to the four categories were determined by using the C5.0 algorithm.

This FMC model can provide a strategic development method for the pharmaceutical industry to conduct market segmentation. The findings may assist pharmaceutical companies provide customized services to health care institutions and to manage their downstream demand effectively.