Understanding Customers Retrial in Call Centers: Preferences for Service Quality and Service Speed
40 Pages Posted: 21 Sep 2016 Last revised: 18 Dec 2020
Date Written: September 14, 2016
Problem Definition: When failing to receive a satisfactory resolution from a call center in the first contact, customers are likely to initiate retrial calls. According to industry reports, retrials are listed as a top annoying issue for customers and hurt call centers' profits. Though recognizing this problem, call centers find it difficult to reduce retrials without overshooting their operating expenses. Our research aims to empirically understand the mechanism of customers' retrials and then provide economically feasible solutions to reduce retrials.
Academic / Practical Relevance: Little empirical research has been done to understand customers' strategic retrials, while theoretical research studies retrials by assuming the degree to which pick-up speed and service quality impact retrials. Our research empirically investigates the mechanism of customers' retrials by studying whether speed and quality truly matter; if so, how strong the impact is from each of them; and whether the impacts are different across various customer segments. The quantified mechanism can then guide service providers to reduce retrials cost-effectively.
Methodology: We use a random-coefficient dynamic structural model to characterize customers' decisions in pursuing a satisfactory resolution and estimate the parameters from call-by-call records of a uniquely designed call center. Our model tracks customers' decisions in the online-waiting stage, where customers are waiting for an agent but weighing whether to abandon, and in the offline-waiting stage, where customers are not directly connected but are actively debating whether to retry. Utilizing the hybrid system that sequentially places customers into queues for three distinct-quality service groups, we disentangle the effects of pick-up speed and service quality on customers' abandonment and retrial decisions.
Results: Our estimations confirm that high service quality and quick pick-up speed reduce retrials. Moreover, we discover that private customers are more sensitive to quality but less sensitive to speed compared to business customers. We suggest two service designs to reduce retrials cost-effectively by tailoring services to customer preferences. One reallocates the service groups for different customer segments without expanding the system, and the other adjusts the staffing ratios by hiring low-cost ordinary-quality agents. Under the two tailoring designs, business customers' surplus increases by up to 13.1% and private customers' surplus by up to 14.9%.
Managerial Implications: First, our research highlights the importance of recognizing customers' offline decisions, which are impacted by online service offerings and will in turn affect future online service operations. Neglecting customers' retrials leads to sub-optimal service designs. Second, by understanding the mechanism of customers' retrials empirically, our research guides call centers to reduce retrials cost-effectively with speed-quality balance. Third, our research develops a structural analysis framework for service providers to quantify customers' preferences and then design tailoring services to improve customers' surplus efficiently.
Keywords: retrials; first-contact resolution; customer services; service speed and quality; call centers; empirical operations management; structural model
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