Customer relationship management: Computer-assisted tools for customer lifetime value prediction

A customer lifetime value (CLV) can be used as an indicator for assessing a customer's worthiness. It is often used among the medium to large organizations for predicting future revenues from their customers. Many research projects have been conducted to enhance the individual prediction models and formulae. However, there are no obvious formal approaches to ensure the consistency and customizability of a prediction process and its major elements. This paper proposes a basic set of computer-assisted tools for a CLV prediction process. The semi-automated tools could be used by the business analysts of an organization to customize the existing templates; record, monitor, and track the work done in each phase of the process. In this paper, various challenges are discussed together with their possible solutions. The tools are specifically designed and implemented for the derivation of customizable formulae and models among the different customer segments of a non-profit organization. In the near future, more research work would be conducted to enhance the capabilities of the tools to cater for possible collaborative CLV predictions among the interested parties on the variables, algorithms, and the subsystems of a model base management system and the associated knowledge base management system.