Customer Segmentation using Machine learning Techniques

Abstract

The rapid expansion of e-commerce resulted in the influx of data in the mainstream. The data of customers can lead to better results and can help the stakeholders to take better results and improve their business. Machine learning also found its application in the e-commerce. Machine learning provides a vast collection of algorithms that produce efficient results in segmenting the customers. In this research paper, we explore e-commerce dataset to perform the segmentation of customers. We used ensemble technique to classify the customers using Support vector Machine (SVC), Logistics Regression, KNear st Neighbors, Decision Tree, Random Forest, AdaBoost Classifier and Gradient Boosting Classifier. We performed in dept analysis on the dataset, studying behaviors and forming clusters. In results, the ensemble model of ensembled Random Forest, Gradient Boosting and k-Nearest Neighbors gave 76.83 % precision.