AI and Analytics for Business
Research Paper Series
Portfolio Dynamics for Customers of a Multi-Service Provider
Multi-service providers, such as telecommunication and financial service companies, can benefit from understanding how customers’ service portfolios evolve over the course of their relationships. This can provide guidance for managerial issues such as customer valuation and predicting customers’ future behavior, whether it is acquiring additional services, selectively dropping current services, or ending the relationship entirely.
In this research, we develop a dynamic hidden Markov model to identify latent states that govern customers’ affinity for the available services through which customers evolve. In addition, we incorporate and demonstrate the importance of separating two other sources of dynamics: portfolio inertia and service stickiness. We then examine the relationship between state membership and managerially relevant metrics, including customers’ propensities for acquiring additional services or terminating the relationship, and CLV.
Through a series of illustrative vignettes, we show that customers who have discarded a particular service may have an increased risk of canceling all services in the near future (as intuition would suggest), but also may be more prone to acquire more services, a provocative finding of interest to service providers. Our findings also emphasize the need to look beyond the previous period, as utilized in much current research, and consider how customers have evolved over their entire relationship in order to predict their future actions.
Keywords: Customer Relationship Management, Dynamic Hidden Markov Model, Customer Value