Abstract

Recently, predicting the buying behaviour of customers on e-commerce websites is a very critical issue in business management. This could help merchants understand the tendencies of consumers in choosing and buying products. It has become increasingly common these days that predicting buying behaviour on online systems. Although this is a challenging task, it is an exciting and hot topic for researchers. This article intends to be proposed as a predictive model for buying behaviour on online systems. This model may be represented as a two-stage process. First, a sequence database is built from a shopping cart. Second, the prediction will be performed by using the CPT+, which is an improved model of CPT (Compact Prediction Tree). The main contribution of this paper is that we proposed a solution for predicting buying behaviour in the e-commerce context (a case study of an e-commerce company). The core prediction is mainly based on sequence prediction, in particularly, CPT+ (Compact Prediction Tree).

Keywords: Sequence prediction, customer behaviour prediction, compact prediction tree, CPT, CPT+, E-commerce.