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Measuring price promotion effects: an econometric exercise in measuring the impact of marketing decision making

Author: Smyth, Stephen ; Wertenbroch, KlausINSEAD Area: MarketingPublisher: Fontainebleau : INSEAD, 2006.Language: EnglishDescription: 3 p.Type of document: INSEAD CaseNote: Latest version available via https://publishing.insead.eduAbstract: One of the key problems in marketing decision making is how to measure the effectiveness of marketing actions, for example, the effect of temporary price promotions on sales. Many outcomes of marketing decisions are multiply determined and involve both short- and long-term effects that are hard to pin down. So marketing managers are often unable to specify the precise effects of what they are doing, and instead rely on intuitive estimates of the effects of their decision making or, worse, on commonsensical arguments to complement ill-conceived cost-plus pricing approaches. Scanner data-based records of customer purchase decisions provide a wealth of data that managers could use, but how can they get useful input for their decision making out of thousands and thousands of purchase transactions?Pedagogical Objectives: This exercise provides students with a hands-on tool to measure the effect of price promotions. It allows students to work with real store-level scanner data of the sort that retailers are collecting store-by-store on a weekly basis. Students estimate regular and promotional price elasticities of demand for two disguised soft drink brands.
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Latest version available via <a href=https://publishing.insead.edu>https://publishing.insead.edu</a>

This exercise provides students with a hands-on tool to measure the effect of price promotions. It allows students to work with real store-level scanner data of the sort that retailers are collecting store-by-store on a weekly basis. Students estimate regular and promotional price elasticities of demand for two disguised soft drink brands.

One of the key problems in marketing decision making is how to measure the effectiveness of marketing actions, for example, the effect of temporary price promotions on sales. Many outcomes of marketing decisions are multiply determined and involve both short- and long-term effects that are hard to pin down. So marketing managers are often unable to specify the precise effects of what they are doing, and instead rely on intuitive estimates of the effects of their decision making or, worse, on commonsensical arguments to complement ill-conceived cost-plus pricing approaches. Scanner data-based records of customer purchase decisions provide a wealth of data that managers could use, but how can they get useful input for their decision making out of thousands and thousands of purchase transactions?

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