We examine the situation in which hourly data are available for designing advertisingresponse models, whereas managerial decision-making can concern hourly, daily or weekly intervals. A key notion is that models for higher frequency data require the intra-seasonal heterogeneity to be addressed, while models for lower frequency data are much simpler. We use three large, actual real-life datasets to analyze the relevance of these additional efforts for managerial interpretation and for the out-of-sample forecast accuracy at various frequencies.

Advertising effectiveness, Advertising response, Aggregation, Normative and predictive validity
International Journal of Forecasting
Department of Econometrics

Kiygi-Calli, M., Weverbergh, M, & Franses, Ph.H.B.F. (2017). Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve. International Journal of Forecasting, 33, 90–101. Retrieved from http://hdl.handle.net/1765/132303