Application of Clustering Algorithm for Effective Customer Segmentation in E-Commerce

Abstract

Due to the huge volume of customers in market and many platforms used by customers for purchasing, the focus turns to e-commerce organizations. It has become important for an organization to segment and cluster their customers and thereby take essential actions to survive against other competitive organizations. Since there are so many options, each organization must satisfy the demands of their customers or they might lose them to other alternatives that already exist in the market. Since the digital market is growing at a lightning speed the requirement of providing a complete experience to users becomes even more essential. In this paper, the dataset of an ecommerce site has been taken to identify all the parameters for analysis, few of them are - date, customer id, product category, payment method, value, time onsite, clicks InSite. The focus of this paper is to analyse the database on above defined parameters by using K-Mean algorithm. Every business in the market should have an effective strategy to address the people and retain their profitable users for its growth. Nowadays, users need personalisation therefore it has now become a need to prioritize experiences or you can’t stand against competitors. Summing up, the paper focuses on introducing customer segmentation, it’s basics, explaining why it is needed in the digital market, filtering the customer data effectively and analysis.