Customer Segmentation Using Machine Learning to Improve Marketing

Abstract

Customer segmentation is the process of classifying customers according to characteristics they have in common. This enables organizations to effectively and accurately market to each group. In business-to-business marketing, a firm may divide its clientele based on a variety of criteria, such as location, industry, number of employees, and previous purchases made from the business. Marketers can more effectively target different audience subsets with their marketing efforts by using segmentation. These initiatives may pertain to product development as well as communications. In particular, segmentation aids in a business's ability to craft and deliver marketing communications that are specifically intended to appeal to some client segments while excluding others. Search and select the most effective communication channel. Based on the segmented clusters, this could be radio advertising, social media (Instagram, Telegram, Twitter, Youtube, etc.) email, or another strategy. We have used Gradio (an API for UI), the KNN Classification Algorithm (to classify new consumers), and the K-Means algorithm (to segment the customers) to accomplish this goal. Determine how to make goods or new opportunities for products or services better. It starts with collecting and evaluating data and concludes with taking suitable and useful action based on the information obtained. Key Words: Segmentation, targeted marketing, K-Means, KNN, Gradio.