Pattern Mining of customer dynamics through different customer value states by using sequence pattern mining and big data analytics

Customers are situated at the center of every business. In fact, they are the pulsating heart of any enterprise, through which revenue streams flow and new customers are attracted. Due to various factors, customer behavior is often complex and uncertain, evolving over time. Therefore, in such circumstances, it is necessary to consider the dynamic nature of customers for analyzing their behavior and devising appropriate strategies. Knowledge and predictions derived from static models are only valid for a specific period and cannot describe the complex and uncertain nature of customer behavior.The aim of this study is to discover dominant patterns of customer dynamics across different value tiers using sequential pattern mining and big data analytics. This research is conducted using customer data from a bank over time. The study focuses on modeling customer dynamics using sequential pattern mining. This approach, by utilizing sequential pattern mining, can assist businesses in planning and improving customer relationship management processes.