A comprehensive survey on customer churn analysis studies

ABSTRACT This paper presents a comprehensive survey of customer churn analysis studies. It begins by examining the customer journey and touchpoints, emphasizing their influence on churn behaviour. The survey then reviews a range of machine learning algorithms used for churn prediction and explores the various feature types employed in this domain. Additionally, it investigates churn analysis across key industries, including telecommunications, banking, and gaming, highlighting the modelling approaches and features commonly applied within each sector. Finally, the paper identifies existing limitations in current research and proposes future directions to address these gaps and associated challenges. Overall, this survey aims to provide a thorough understanding of current practices and to support further advancements in the field of customer churn analysis.