Abstract

In this research paper, authors explore the application of the K-means algorithm and the elbow method in customer segmentation using machine learning techniques. The algorithm is applied to a customer dataset and effectiveness of the resulting customer segments is evaluated. The performance of K-means with other clustering techniques is compare and the impact of different input parameters on the segmentation results is studied. The findings of this study can help businesses to improve their marketing strategies by targeting specific customer segments with customized marketing campaigns.