Indian Banking Precision Marketing: A Comparative Analysis of Machine Learning Customer Segmentation Algorithms

Precision marketing is a crucial technique in the rapidly changing Indian banking industry, as it helps improve client engagement and optimize marketing efforts. This study explores the use of sophisticated machine-learning algorithms to perform complex client segmentation, which enhances personalized marketing strategies to a higher level. This study specifically examines the application and comparative analysis of two important techniques: Recency, Frequency, Monetary value (RFM) combined with K-means clustering, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This study rigorously assesses the efficacy of these techniques using actual transactional data from a prominent private bank in India. These findings have implications that go beyond the realm of finance, providing significant insights for professionals, scholars, and government officials. This research highlights the significant impact of modern analytical techniques on redefining customer engagement tactics in the ever-changing Indian banking market.