RFM high-speed railway customer value classification model based on spark

Abstract

As implementing customer relationship management (CRM) is the future development trend of high speed railway, based on the customer value of customer classification research has important theoretical and realistic significance. Based on the huge number of the high speed railway's customers, this paper proposes a parallel RFM customer value classification model based on the Spark framework. First, based on the RFM customer value model, calculating the coefficient of customer's value, then based on the Spark framework, designing the parallel genetic k-means algorithm. The experiment proved this model has the quality of computing quickly and high precision. It has the obvious practical significance applied to the customer relationship management system.