Modeling intra-seasonal heterogeneity in hourly advertising-response models: Do forecasts improve?

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• 作者：Meltem Kiygi-Calli^a ; ^{meltem.kiygicalli@okan.edu.tr} ; Marcel Weverbergh^b ; ¹ ; ^{marcel.weverbergh@uantwerpen.be} ; Philip Hans Franses^c ; ² ; ^{franses@ese.eur.nl}
• 关键词：Advertising effectiveness ; Advertising response ; Aggregation ; Normative and predictive validity
• 刊名：International Journal of Forecasting
• 出版年：2017
• 出版时间：January-March 2017
• 年：2017
• 卷：33
• 期：1
• 页码：90-101
• 全文大小：645 K
• 卷排序：33

文摘

We 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.