Classification of Customers Based on Classifications of their Category Using Machine Learning

In today's data-driven business world, it is essential for companies trying to gain a competitive edge to understand customer behavior. Customer analysis and segmentation are crucial for customizing goods, services, and marketing strategies to meet varied client wants. In addition to agglomerative segmentation techniques, the proposed unique approach model MRFT examined the largest dataset of e-commerce which is being introduced by Gaussian, K-means, and DBSCAN clustering method. This study uses cutting-edge machine learning techniques, specifically classification algorithms, to assess and categorize customer data into distinct groups. By using the capabilities of algorithms like Random Forest, Support Vector Machines, this research aims to provide businesses with a comprehensive framework for maximizing client targeting and customization methods. The study's conclusions might increase customer satisfaction, increase revenue, and entice loyal customers. The study also looks at the potential, difficulties, and uses of machine learning for real-world customer segmentation applications.