Customer Segmentation Using Machine Learning

Customer segmentation is a technique for targeting customers in order to increase a company's revenue. It is all about collecting the information about the customers and grouping them based on their similarity. To achieve this, we had developed web application using streamlit to make use of k- means algorithm, and then it can be visualized to target the customers. This method is used in business related fields applications. This paper deals with real-time data like customers age and consists of different variables related to its application. Once an algorithm done its task with data, it will complete the task automatically. To complete the task, we had done Python with Machine learning approach. After loading the data, the data gets visualized with the bar plots based on different variables. Important variables are identified. The number of clusters or groups is obtained by the method called Elbow method. These variables are fit into the K-means model. This plot would provide the details and the mentalities of customers, thereby helping the companies to improve the products and techniques to increase their sales.