Can Retail Sales Volatility be Curbed Through Marketing Actions?

For many years, marketing managers have used dynamic sales response models to compute expected sales conditional on the available information. These models fail to recognize that the volatility conditional variance of sales can vary over time. Moreover, the covolatilities conditional covariances between sales and marketing-mix variables can be time varying. Both concepts introduce a new range of strategic and tactical considerations for product and brand managers. Using a multivariate volatility model, we investigate the covolatility of sales and the marketing mix of a focal brand and competing brands in the market. We also examine carryover effects from a volatility perspective. The methodology is applied to six product categories sold by Dominick's Finer Foods. The results reveal valuable implications for marketing managers. Data and the online appendix are available at https://doi.org/10.1287/mksc.2016.1013 .

[1]  Dominique M. Hanssens,et al.  Market Response Models: Econometric and Time Series Analysis , 1989 .

[2]  Garrett J. van Ryzin,et al.  Strategic Capacity Rationing to Induce Early Purchases , 2008, Manag. Sci..

[3]  Tasadduq A. Shervani,et al.  Market-Based Assets and Shareholder Value: A Framework for Analysis , 1998 .

[4]  J. Raju.  The Effect of Price Promotions on Variability in Product Category Sales , 1992 .

[5]  W. Reinartz,et al.  The impact of internal and external reference prices on brand choice: The moderating role of contextual variables , 1998 .

[6]  Kapil R. Tuli,et al.  Customer Satisfaction and Stock Returns Risk , 2009 .

[7]  David A. Matsa.  Competition and product quality in the supermarket industry. , 2011, The quarterly journal of economics.

[8]  Marc Fischer,et al.  Brand Performance Volatility from Marketing Spending , 2015, Manag. Sci..

[9]  R. Rust,et al.  The Effect of Customer Satisfaction on Consumer Spending Growth , 2010 .

[10]  Andrew T. Ching,et al.  Consumer Learning and Heterogeneity: Dynamics of Demand for Prescription Drugs after Patent Expiration , 2001 .

[11]  R. Engle.  Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation , 1982 .

[12]  Dominique M. Hanssens,et al.  Sustained Spending and Persistent Response: A New Look at Long-Term Marketing Profitability , 1999 .

[13]  Paul R. Milgrom,et al.  Price and Advertising Signals of Product Quality , 1986, Journal of Political Economy.

[14]  R. Engle,et al.  Multivariate Simultaneous Generalized ARCH , 1995, Econometric Theory.

[15]  Christian Homburg,et al.  Customer Satisfaction, Analyst Stock Recommendations, and Firm Value , 2010 .

[16]  Dominique M. Hanssens,et al.  Order forecasts, retail sales, and the marketing mix for consumer durables , 1998 .

[17]  Dominique M. Hanssens,et al.  New Products, Sales Promotions, and Firm Value: The Case of the Automobile Industry , 2004 .

[18]  Vineet Padmanabhan,et al.  Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect" , 1997, Manag. Sci..

[19]  Ajay K. Kohli,et al.  Ties that Bind: The Impact of Multiple Types of Ties with a Customeron Sales Growth and Sales Volatility , 2010 .

[20]  J. Avery,et al.  The long tail. , 1995, Journal of the Tennessee Medical Association.

[21]  C. Fornell,et al.  Customer Satisfaction and Shareholder Value , 2004 .

[22]  Helmut Ltkepohl,et al.  New Introduction to Multiple Time Series Analysis , 2007 .

[23]  Kevin Sheppard,et al.  MFE MATLAB Function Reference Financial Econometrics , 2009 .

[24]  Demetrios Vakratsas,et al.  The effects of advertising, prices and distribution on market share volatility , 2008, Eur. J. Oper. Res..