Customer Market Segmentation using Machine Learning Algorithm

Abstract

Everything is becoming more mechanized in today's times, especially in this age of data. Data is the world's new electricity. Many firms can benefit from this information in their marketing efforts. Every company wanted to grow and be better than the competition, so they employed innovative ideas and invested in product development, but only to keep their customers and expand their market. Customers are segmented in today's commercial world. They analyze their consumers' behaviors and purchasing patterns and can assist them in generating profit. Customer segmentation refers to the process of categorizing a company's customers into groups based on their commonalities. Client segmentation is the process of determining how to interact with consumers in different groups to amplify the value of each customer to the company. Unsupervised machine learning is used to segment customers. There are many algorithms that can partition customers based on their behavior and other parameters, and our study's main goal is to cluster customers into various clusters based on their behavior patterns. This research study has compared five clustering algorithms and selected the best of them for further research.