G.Nishith Reddy, G.Sai Karthik, M.Priyanka and J. Spandana
In the dynamic realm of e-commerce, where customer retention is paramount, predicting customer attrition becomes a crucial aspect for ensuring business sustainability and growth. This study introduces an innovative machine learning model designed to provide precise forecasts of customer attrition. Utilizing a meticulously curated dataset extracted from An online retail (E commerce) company, the model employs advanced algorithms to discern patterns indicative of potential churn. By integrating predictive analytics, the model equips e-commerce businesses with a proactive means to implement targeted strategies, such as personalized promotions and enhanced customer service, thus mitigating the risk of losing valuable customers. This research not only contributes to optimizing customer retention efforts in the e-commerce ecosystem but also sheds light on the evolving landscape of customer dynamics, emphasizing the necessity of adaptive strategies in an ever-changing market.
E-commerce, Customer behaviour, Customer churn, Predictive analytics, Customer retention.