Authors: Niravkumar Mahendrabhai Panchal
Abstract: Customer churn has become a major challenge for global e-commerce businesses due to increasing market competition and changing consumer behaviour. This study examines the role of machine learning and big data analytics in predicting customer churn and improving customer retention strategies. A quantitative research design with secondary data sources was adopted to analyse customer behaviour patterns and predictive modelling techniques. The findings indicate that machine learning algorithms and predictive analytics significantly improve churn prediction accuracy and support personalised customer engagement strategies. The study highlights the importance of data-driven decision-making in international e-commerce and provides practical insights for improving customer loyalty, profitability, and long-term business sustainability.
DOI: http://doi.org/10.5281/zenodo.20646827
