Kiygi-Calli, MeltemWeverbergh, MarcelFranses, Philip Hans2024-05-252024-05-2520170169-20701872-820010.1016/j.ijforecast.2016.06.0052-s2.0-84992153598https://doi.org/10.1016/j.ijforecast.2016.06.005https://hdl.handle.net/20.500.14517/215Kiygi-Calli, Meltem/0000-0002-2979-9309; Franses, Philip Hans/0000-0002-2364-7777We examine the situation in which hourly data are available for designing advertising response 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. (C) 2016 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.eninfo:eu-repo/semantics/openAccessAdvertising effectivenessAdvertising responseAggregationNormative and predictive validityArticleQ1Q133190101WOS:0003910803000072