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Modeling and Analysis of Call Center Arrival Data: A Bayesian Approach

Department of Decision Sciences, School of Business, The George Washington University, Washington, D.C. 20052
Department of Decision Sciences, School of Business, The George Washington University, Washington, D.C. 20052
soyer{at}gwu.edu
muratt{at}gwu.edu

In this paper, we present a modulated Poisson process model to describe and analyze arrival data to a call center. The attractive feature of this model is that it takes into account both covariate and time effects on the call volume intensity, and in so doing, enables us to assess the effectiveness of different advertising strategies along with predicting the arrival patterns. A Bayesian analysis of the model is developed and an extension of the model is presented to describe potential heterogeneity in arrival patterns. The proposed model and the methodology are implemented using real call center arrival data.

Key Words: call center; advertising strategy; modulated Poisson process; Bayesian analysis; heterogeneity
History: Received: October 29, 2004;