Using Employing K-Means Clustering Algorithm for Sophisticated Visualization of a Bank's Credit Card Data Landscape

Abstract

Due to the emergence of numerous entrepreneurs with startup ideas and competitors, the new businesses are in significant need of exploring tools and technologies to figure out new buyers and at the same time to keep the older ones as well. Customer segmentation using k mean clustering is an imperative technique to separate the customers into targets segments which can help the businesses to apply marketing strategies accordingly. This can also help in providing exceptional customer services. The research is based on analyzing the dataset of a bank to estimate the customer segmentation of a credit card by proposing a model to help company define its marketing strategies. K-mean algorithm has been used for dividing the group of customers in to segments in the form of clusters by determining the value of k through a silhouette technique. For better visualization Principal Component analysis has been used for dimensionality reduction and to achieve better results by implementing better visualization in Jupiter notebook.