Effect of Brand Loyalty on Advertising and Trade Promotions: A Game Theoretic Analysis with Empirical Evidence
AbstractIn this paper we examine the issue of balancing media advertising (pull strategy) and trade promotions (push strategy) for manufacturers of consumer packaged goods utilizing a three-stage game theoretic analysis and test model's implications with scanner panel data. We develop a model of two competing manufacturers who distribute their brand to consumers through a common retailer. In the model the manufacturers directly advertise their brand to consumers and also provide trade deals to the retailer. Each manufacturer's brand has a loyal segment of consumers who buy their favorite brand unless the competing brand is offered at a much lower price by the retailer. The number of loyal consumers is different for the two brands and so is the strength of their loyalty to their favorite brand. The loyal consumers of the brand with stronger loyalty require a larger price differential in favor of the rival brand before they will switch away from their favorite brand. The manufacturers first decide advertising spending level, and then the wholesale price of their respective brands. The two manufacturers do not observe each other's decisions while making these decisions, however they do take into account how the other firm is likely to react as a function of their own decisions. Advertising directly affects the strength of loyalty a consumer has for the favorite brand. If the favorite brand advertises, the loyalty strength increases but if the rival brand advertises, it decreases. The marginal effect of own versus competing brand advertising is different in magnitude. The two manufacturers provide trade deals to the retailer by discounting the brand from a regular wholesale price. The trade discounts are partially passed on to the consumers by the retailer who sets the retail prices of the two brands after observing the wholesale prices. The retail shelf price discounts make the promoted brand more attractive to the consumers due to the reduced price differential between their favorite brand and the promoted brand, thus affecting their switching behavior. The model and its analysis shed light on the role of brand loyalty in the optimal advertising and trade promotion policies for the two manufacturers. The analysis indicates that, if one brand is sufficiently stronger than the other and if advertising is cost effective, then the stronger brand loyalty requires less advertising than weaker brand loyalty, but a larger loyal segment requires more advertising than a smaller loyal segment. Moreover, stronger brand loyalty requires more trade promotion spending under these conditions. The analysis also indicates that the retailer promotes the stronger loyalty brand more often but provides a smaller price discount for it compared to the weaker loyalty brand. These analytical results can be understood better if we view advertising as a “defensive” strategy used to build brand loyalty which helps in retaining the loyal consumers, and price promotions as an “offensive” strategy used to attract the loyal consumers away from the rival brand. For example, the result that the stronger brand invests less in advertising than the weaker brand can be explained as follows. The stronger loyalty brand does not find use of advertising attractive because it faces little threat from the weaker brand due to its sufficiently stronger loyalty. Instead it spends more on promotions (provided advertising is cost effective) to attract away the weaker brand's loyal consumers. The weaker brand, on the other hand, finds it optimal to defend its loyal franchise by spending more on advertising, as promotions do not help much due to the difficulty in attracting away the stronger brand's loyal consumers. In this sense, the stronger brand plays “offensive” by using more trade promotions, and the weaker brand plays “defensive” by emphasizing advertising. We also conduct an empirical analysis of the model's propositions using scanner panel data on seven frequently purchased nondurable product categories. In a sample of 38 national brands from the seven categories we find that weaker loyalty brands spend more on advertising; brands with larger loyal segment spend more on advertising; and the retailer promotes stronger loyalty brands more often but provides a smaller price discount on average for them compared to weaker loyalty brands. These findings are consistent with the model.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Marketing Science.
Volume (Year): 15 (1996)
Issue (Month): 1 ()
advertising; brand loyalty; game theory; promotional mix;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Huang Rui & Perloff Jeffrey M & Villas-Boas Sofia B, 2006.
"Effects of Sales on Brand Loyalty,"
Journal of Agricultural & Food Industrial Organization,
De Gruyter, vol. 4(1), pages 1-26, July.
- Huang, Rui & Perloff, Jeffrey M. & Villas-Boas, Sofia B, 2006. "Effect of sales on brand loyalty," CUDARE Working Paper Series 1011R, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
- Huang, Rui & Perloff, Jeffrey M & Villas-Boas, Sofia B, 2006. "Effect of Sales on Brand Loyalty," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2qc1p7g9, Department of Agricultural & Resource Economics, UC Berkeley.
- Berck, Peter & Brown, Jennifer & Perloff, Jeffrey M. & Villas-Boas, Sofia B, 2007.
"Sales : tests of theories on causality and timing,"
CUDARE Working Paper Series
1031, University of California at Berkeley, Department of Agricultural and Resource Economics and Policy.
- Berck, Peter & Brown, Jennifer & Perloff, Jeffrey M & Villas-Boas, Sofia B., 2007. "Sales: Tests of Theories on Causality and Timing," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2g56n1jk, Department of Agricultural & Resource Economics, UC Berkeley.
- Sheng, Li, 2010. "Competing or cooperating to host mega events: A simple model," Economic Modelling, Elsevier, vol. 27(1), pages 375-379, January.
- Chih-Jen Wang & Ying-Ju Chen & Chi-Cheng Wu, 2011. "Advertising competition and industry channel structure," Marketing Letters, Springer, vol. 22(1), pages 79-99, March.
- Karray, Salma, 2013. "Periodicity of pricing and marketing efforts in a distribution channel," European Journal of Operational Research, Elsevier, vol. 228(3), pages 635-647.
- González-Benito, Óscar, 2004. "Random effects choice models: seeking latent predisposition segments in the context of retail store format selection," Omega, Elsevier, vol. 32(2), pages 167-177, April.
- Allender, William J. & Richards, Timothy J., 2009. "Measures of Brand Loyalty," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin, Agricultural and Applied Economics Association 49536, Agricultural and Applied Economics Association.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.