Enhancing Customer Churn Analysis in E-Commerce Platforms through Federated Learning: A Data-Centric Approach

Abstract

E-commerce platforms have always been of a huge demand overall in the whole world. Earning money in the current generation has become easier than before. Due to the rapid development in the industry by connecting people has paved the way for various patterns. Ecommerce platforms have undergone rapid development due to the increasing usage of the internet. On the other hand it is crucial and important to know how a particular customer would go about the platform and make specific purchases according to the seasonal change. It is most widely said that the customer is the king. Knowing the type of purchases that take place during these seasons would help vendors and retailers make appropriate decisions. In this project we would be doing analysis on the purchase patterns with the help of data analysis and then we would move on to proposing a solution on how vendors and retailers could understand the purchase pattern of customers in a detailed oriented approach with the help of federated learning.

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