The Role of Predictive Analytics in Enhancing Customer Retention Strategies in E-commerce

Abstract

In the ever-evolving dynamic environment of e-commerce, customer retention has become one of the main themes for any long-term successful business. This study will reveal some opportunities for applying Predictive analytics to improve customer retention strategies against such a big problem, which usually stands five to twenty-five times cheaper than acquiring new customers. This is a mixed-methods approach, including qualitative case studies intertwined with the quantitative analysis of empirical data from varied industries in e-commerce, such as fashion retail and online marketplaces. It, therefore, implies a strong positive correlation between the application of predictive analytics and customer retention rates. Businesses can use historical data and statistical algorithms to identify potential churning customers, developing targeted marketing campaigns to make them stick with the personal touch of customer experience. This study creates a financially viable impact by emphasising big data analytics, artificial intelligence, and focused marketing strategies toward creating customer value. The results denote that companies that have been able to apply predictive analytics enjoy customer satisfaction and create a better stronghold on the market. Theoretically and practically, this study contributes to an understanding of customer retention in e-commerce and aids businesses in how to apply effective practical predictive analytics strategies.