Abstract
With the increasingly fierce competition among enterprises, it is important for enterprises to understand customer behaviors accurately in a dynamic environment. While data mining methods have been applied to investigate customer behavior patterns with high-quality objective data, the process perspective has been largely neglected. Given that customer behaviors can be reflected in process event logs, it is possible to mine the real behavior patterns from a process-based perspective. To this aim, this paper presents a method for exploring customer behavior patterns using process mining techniques. The method consists of five steps: data collection and preprocessing, customer service process modeling, identifying deviant behaviors, clustering analysis and discovering customer behavior patterns. This method provides a viable way to understand the customer behavior patterns from a process-based perspective.
Recommended Citation
Sun, Wenxue; Huang, Lei; and Wang, Ying, "Exploring Customer Behavior Patterns: A Process-based Perspective" (2020). WHICEB 2020 Proceedings. 31.
https://aisel.aisnet.org/whiceb2020/31