Customer Segmentation in Retailing using Machine Learning Techniques

Having multiple competitors in order to find new buyers and keep existing clients, has resulted in great deal of tension between competing businesses. As a result, offering the best customer service may benefit companies of all sizes. The technique of grouping a client base into several categories based on requests, behavior, money, etc. is known as Customer Segmentation. Whereas product segmentation is the process of classifying products into different categories. The major objective of our study is to divide customers and products into multiple clusters based on different criteria in order to acquire results. There are several algorithms that may partition customers based on various metrics. These are utilized to discover hidden patterns in data, discover valuable, loyal clients, understand consumer purchasing habits, and more. In order to improve decision-making and create the most accurate model possible, cluster analysis is done. This research study has compared seven clustering algorithms and selected the best of them for further analysis