Measuring the Impact of Promotion on Weekly Market Shares
Philip Hans Franses
Erasmus University Rotterdam (EUR) - Department of Econometrics
VU University Amsterdam - Faculty of Economics and Business; Tinbergen Institute
In this paper we propose a simple method to measure the impact of promotional activities on weekly market share. The main idea is to assume that if promotion has an effect, it generates an additive outlier or a temporary level shift in the market share data. We propose an outlier robust estimation technique that can give estimates of the size of such an additive outlier or temporary level shift relative to an outlier-free time series. These estimated sizes then measure the impact of promotion. We illustrate our method for two examples concerning market shares of fast moving consumer products. Two recent surveys on the analysis of the effect of promotional activities on sales and market share in Blattberg and Neslin (1989) and Blattberg, Briesch and Fox (1995) conclude with many interesting questions for further research. One of these involves the design of proper econometric methods to examine static and/or dynamic effects of promotion. In the present paper we aim to contribute to this important research area by proposing a simple econometric time series technique (based on robust estimation methods) that can estimate the net effect of promotion from noisy data. The main idea of our approach is that we assume that promotional activities generate outliers or level shifts in the market share data. We apply our technique to more than two years of weekly scanning data of the market shares of two brands of a fast-moving consumer product. A useful advantage of our approach is that we are able to estimate the so-called "baseline" market share at the time promotion occurred (see Blattberg and Neslin, 1989, p. 89) and also that we can provide confidence intervals for the quantitative effect of promotion. An alternative to our methodology would be to use zero-one dummy variables in a time series regression (see Leone, 1987, for a marketing application of such so-called intervention analysis). Application of our robust technique, however, relieves the practitioner from the burdensome task of specifying the correct delay effects of promotional activities on market share, something which cannot be avoided when using the dummy approach.
JEL Classification: M3, L15, L16
Date posted: January 21, 1998