Customer Segmentation

Abstract

Abstract: Effective marketing involves targeting specific customer groups with personalized products, services, and campaigns, making customer segmentation a crucial strategy in modern business. This paper introduces a pioneering customer segmentation method that utilizes machine learning techniques to accurately and efficiently segment customers based on their behaviors, demographics, and transaction history. By combining transfer learning, Rfm (recency, frequency, monetary) modeling, and clustering algorithms like K-means, our approach generates meaningful customer segments, offering valuable insights for personalized marketing and improved customer experiences. We showcase the positive impact of our method on a real-world dataset, displaying noteworthy enhancements in marketing effectiveness and customer satisfaction.