An Effective Approach to Cluster Customers with a Product Recommendation System

Abstract

Faster development of technology these days has totally changed the nature of a retail business and hence the perspective of customers (consumers) towards shopping. In this current technologydriven world, customers see no distinction between online and offline shopping which means the expectation level of customers is increasing day by day. They need the companies to know what they want and make those products available when they are in need. To achieve this, retailers are in need of a personalization strategy where they get to know the customers better. In this paper, we suggest one such personalization strategy where we predict the various kinds of the customer based on their arrival and purchase of items in the shop. Knowing the behavior of the customer makes the product promotion easier which in turn improves the response rate and hence the sales rate. The other way of gaining profit in retail business is predicting what the customers will buy as per their buying patterns and seasons. This paper also addresses a strategy by which the retailers will know what a customer will buy for next one month.