Tackling Customer Wait Times

Abstract

In the digital age, call centers remain a pivotal touchpoint between businesses and their clientele. They offer direct human interaction that shapes customer experience. One of the primary pain points in this interaction is the wait time a customer endures before being attended to. This research delves into the challenge of minimizing customer wait times in call centers. The authors experiment a blend of traditional optimization techniques and contemporary machine learning methods for the same. By leveraging integer programming, they formulate an optimization problem to efficiently allocate calls to agents. The main objective of the chapter is to reduce the cumulative waiting time while maintaining the customer satisfaction. The authors harness the predictive power of machine learning to forecast call durations based on various parameters as well. Preliminary results indicate a significant potential in combining these approaches. It offers a robust framework for call centers to enhance their operational efficiency. This elevates the customer experience in a very competitive environment as well.