Customer Segmentation Using Hierarchical Agglomerative Clustering

Abstract

Customer segmentation plays an important role in customer relationship management. It allows companies to design and establish different strategies to maximize the value of customers. Customer segmentation refers to grouping customers into different categories based on shared characteristics such as age, location, spending habit and so on. Similarly, clustering means putting things together in such a way that similar type of things remain in the same group. In this study, a machine learning (ML) hierarchical agglomerative clustering (HAC) algorithm is implemented in the R programming language to perform customer segmentation on credit card data sets to determine the appropriate marketing strategies.