Forecasting Call Flow in a Direct Marketing Environment

Peter Varisco

Foresight: The International Journal of Applied Forecasting, 2006, issue 4, pages 11-15

Abstract: Peter provides a case study in the use of dynamic modeling to forecast call volumes and to estimate how these volumes are affected by the timing of direct mail campaigns. Dynamic modeling, variously called dynamic regression, ARIMAX, and transfer function modeling, is a driver-based (explanatory) methodology that can supply precise timing effects of key drivers, such as direct mail promotions. In summarizing the lessons from the application of this methodology at New York Life Insurance, Peter provides a working demonstration of the method's value for call-volume forecasting. Copyright International Institute of Forecasters, 2005

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