Enablıng Machınes To Predıct Customer Behavıor Usıng Votıng-Classıfıer Technıque

Abstract

In the retail industry, understanding existing customers' behavior based on their buying behavior is one thing that can drive business from bottom to top. Customer on an individual basis as well as on a collective basis shows his/her interest towards particular business products, interest being personal or towards the best product of that business. At an initial level, some businesses succeeds in understanding their customer needs and behavior but when businesses grow up and ready to expand, they need some powerful technologies that can do work for them for such a huge amount of customer data. In this paper, we have discussed a technique to segment customers in different categories based on their past behavior and then built a voting classifier model to predict what items a particular customer will buy in future transactions.