Customer behaviour classification using majority based ensemble voting classifier

Customer segmentation is to collect customer related data to generalize some insight so as to solve business challenges. Data like when customer is purchasing, how many times they have purchased, how much they have spent ,which product is purchased in huge quantity, which country has highest sales of particular product. After getting all the details most of the companies or business industry provides, customer related market activity which will help not only companies but also customers too which leads to growth of business. Through understanding the customer behaviour using their buying patterns we can easily focus on our valuable and churning customers. In this paper, we have studied the behaviour of past customer using segmentation process, RFM model, k means clustering and build a voting classifier model to predict what item a customer can buy in future.