Forecasting volumes for trade promotions in CPG industry using market drivers
ABSTRACT Promotions are an integral part of the consumer packaged goods (CPG) industry. Anywhere between 30-40% of the sales volumes are achieved through various promotions. Promotions are instrumental in creating brand visibility and awareness. In this study, we attempt to analyse the impact of promotions with feature advertises, in-store display, temporary price discounts etc. Five different multivariate regression models have been developed to forecast the total sales of a product considering pricing and distribution variables. The performance of these models has been analysed by using syndicated data. Based on the results, it is found that the S-shaped (double-log) model has shown superior performance over the other models considered in this study.
SourceAvailable from: Dominique Hanssens[Show abstract] [Hide abstract]
ABSTRACT: The use of price promotions to stimulate brand and firm performance is increasing. We discuss how (i) the availability of longer scanner data time series, and (ii) persistence modelling, have lead to greater insights into the dynamic effects of price promotions, as one can now quantify their immediate, short-run, and long-run effectiveness. We review recent methodological developments, and illustrate how the analysis of numerous brands and product categories has resulted in various empirical generalizations. Finally, we argue that persistence modelling should not only be applied to traditional performance metrics such as sales, but also to metrics such as firm value and customer equity. Copyright © 2005 John Wiley & Sons, Ltd.Applied Stochastic Models in Business and Industry 07/2005; 21(4‐5):409 - 416. DOI:10.1002/asmb.581 · 0.53 Impact Factor
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ABSTRACT: Market response models are intended to help scholars and managers understand how consumers individually and collectively respond to marketing activities, and how competitors interact. Appropriately estimated effects constitute a basis for improved decision making in marketing. We review the demand and supply of market response models and we highlight areas of future growth. We discuss two characteristics that favour model use in practice, viz. the supply of standardized models and the availability of empirical generalizations.Marketing as a discipline and market response models as a technology may often not receive top management attention. In order to have enhanced relevance for senior management, we argue that marketing models should be cross-functional, include short- and long-term effects, and be considerate of capital markets. We also identify emerging opportunities for marketing model applications in areas such as public policy and litigation. Copyright © 2005 John Wiley & Sons, Ltd.Applied Stochastic Models in Business and Industry 07/2005; 21(4‐5):423 - 434. DOI:10.1002/asmb.584 · 0.53 Impact Factor