Customer Clustering Using K-Means

Abstract

Customer Segmentation analyzes customers interacting with the company and its product. Here, behavior depends on the money they spend and the frequency of buying.  To grow a business efficiently, it is essential to analyze the market’s competition and identify customer patterns timely. To do so, customers are divided into groups with different characteristics, like customers who spend more money and are more frequent those who spend less money and are less frequent than others. Using the above data, companies can then outperform the competition in the market by developing products and services according to customer needs. The above analysis is done using the “k-means” clustering, an unsupervised machine learning algorithm. K-means divides customer data into different clusters based on their spending habits.