Customer Segmentation in E-Commerce to Retain and Gain the Customers

Abstract

Nowadays, industries adopt data science to better understand their customer’s activity and differentiate their offerings from their competitor. For deploying customer segmentation in e-commerce, data mining approaches like clustering and subgroup discovery will be used. Combining new marketing strategies with word-of-mouth recommendations is become very important for making any successful business model. Due to a large diversity of products, their features, and sales makes it difficult to find the patterns of customer’s preferences. For achieving optimum segmentation, we used the clustering techniques to classify the customers based on their online purchasing based on different categories. The goal of this paper how the customer makes purchasing patterns and divides them into segments on which we can enable practitioners for term profitability by retaining and gaining the customers. It may also help e-commerce companies in their business model to retain and gain customers.