Improving Effectiveness of Customer Service in a Cost-Efficient Way - Empirical Investigation of Service Allocation Decisions with Out-Sourced Centers

Ever since the 1990s, the role of call centers has been transformed from simply dealing with customer inquiries to performing integrated marketing functions. Firms are starting to view contemporary call centers as preferred and prevalent channels to acquire and retain customers, enhance customer relationship and grow long-term revenue, rather than a cost to be minimized. The management of call centers has become an important part of customer relationship management (CRM) strategy. However, the management of call centers has always remained the research topic of operation management, which focuses on minimizing operating cost and often ignores the resulting customer reactions and financial implications. In this paper, we treat service duration as a measurement of operating cost (operating efficiency), as well as a determinant of customer retention (marketing effectiveness). Given both operating cost and marketing consequences are driven by allocation decisions, we propose a dynamic structural framework that allows the firm to learn about the heterogeneous preference of customers as well as the comparative advantages of off-shore centers, balance the trade-offs between short term cost benefit and long term customer reactions, and make optimal allocation decisions that best match customer preference for service duration and maximize long-term profit. Thus, the traditional operation management problem of call allocations is formulated as a customer relationship management problem in which the firm is allowed to incorporate marketing consequences into operating decisions to grow customer relationship. Applying the proposed framework to customer call history data provided by a high tech company that operates off-shore service centers, we first estimate the model to parameterize the relationship among call allocation, service duration, customer retention and profit as well as that between short-term cost benefit and long-term marketing consequences. Based on the estimation results, we then conduct simulations to derive the optimal service allocation decisions. We next establish the dynamic, customized, and state-dependent nature of the derived optimal operating decisions and show how they are driven by marketing consequences. Finally, we demonstrate that by taking into account long-term marketing consequences, the optimal allocation decisions derived from our framework (1) improve customer retention; (2) reduce service costs; and (3) enhance profit by growing relationships. In short, the effectiveness can be improved in an efficient way. Our findings shed new light on the understanding of marketing consequences of service operation decisions. The estimation and simulation results provide directional guidance and analytical solution to improve service allocation decisions for call-center managers who plan to accommodate customer relationship to their operating decisions. The developed adaptive learning rule and optimization solutions provide the computational algorithm to automate the implementation of service allocations for firms that can integrate their CRM system and operating system.