Document Type : Original Article
Authors
1
Ph.D. Candidate, Department of Information Technology Management, NT.C., Islamic Azad University, Tehran, Iran.
2
Associate Professor, Department of Industrial Engineering, NT.C., Islamic Azad University, Tehran, Iran.
3
Associate Professor, Department of Industrial Management, NT.C., Islamic Azad University, Tehran, Iran.
Abstract
Customer behavior in banking electronic payments is dynamic and time-dependent, and customers may shift between different behavioral states throughout their lifecycle. Despite the widespread use of the Recency, Frequency, and Monetary (RFM) model for customer segmentation, a significant portion of previous studies has performed this analysis cross-sectionally, with limited attention to the temporal dynamics of behavior and customer transitions between behavioral segments. Therefore, understanding the gradual paths of customer behavior change remains a gap.
This study aims to analyze the dynamics of customer behavior by examining 20 months of transactional data from all customers of a private commercial bank. Based on indicators derived from the Recency, Frequency, Monetary, and Cost (RFMC) framework, five distinct behavioral states were identified, and customer transitions between these states were analyzed over consecutive periods. The findings indicate that customer behavior is heterogeneous and transformable, with varying levels of stability across different behavioral states. Declines in customer activity generally occur gradually through intermediate states, and direct transitions from high-engagement states to inactive states are limited. Additionally, some customers were observed to return from low-activity or inactive states to higher levels of engagement, indicating the non-linearity of behavioral paths. The results of this research show that analyzing temporal transitions alongside behavioral segmentation provides a more accurate picture of the customer lifecycle and can serve as a basis for monitoring behavioral changes and designing targeted actions in customer relationship management.
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