Preliminary Studies on Predicting Customer Purchase Behaviour in Online Retail Business

Abstract

Online retail business has become a popular trend in our life because it is very easy and hassle free. The increasing amount of customer in online retail business motivates the use of data mining techniques to discover the customer purchase behaviour. Before the implementation of data mining technique, the problems encountered by the online retail business are time consuming, probable human error and space consumption. These problems have degraded the rate of customer purchase in online retail business. Therefore, the objective of this research is to identify the existing methods in predicting customer purchase behaviour. The recency, frequency and monetary (RFM) based classification techniques are proposed to model the customer purchase behaviour. Next, the results obtained from the proposed models are predicted using correlation and linear regression methods to predict the customer purchase behaviour. The result from the end of the research will be further discussed. Various technique can be applied to further improve the current result in future work.