# Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications

- 644 Downloads
- 5 Citations

## Abstract

This paper investigates the dynamic effects of price promotions in a retail setting through the use of a large-scale field experiment varying the promotion depths of 170 products across 17 categories in 10 supermarkets of a major retailer in Chile. In the intervention phase of the experiment, treated customers were exposed to deep discounts (approximately 30%), whereas control customers were exposed to shallow discounts (approximately 10%). In the subsequent measurement phase, the promotion schedule held discount levels constant across groups. We find that treated customers were 22.4% more likely to buy promoted items than their control counterparts, despite facing the same promotional deals. Strikingly, the magnitude of the dynamic effects of price promotions (when promotional depths are equal across conditions) is 61% of the promotional effects induced by offering shallow vs. deep discounts during the intervention phase. The result is robust to other concurrent dynamic forces, including consumer stockpiling behavior and state dependence. We use the experimental variation and historical promotional activities to inform a demand-side model in which consumers search for deals, and a supply-side model in which firms compete for those consumers. We find that small manufacturers can benefit from heightened promotion sensitivity by using promotions to induce future consideration. However, when unit margins are high, heightened promotion sensitivity leads to fierce competition, making all firms worse off.

## Keywords

Price promotions Dynamic effects Consumer search Bertrand supertraps Field experiments## References

- Anderson, E.T., & Simester, D.I. (2004). Long-Run Effects of promotion depth on new versus established customers: Three field studies.
*Marketing Science*,*23*(1), 4–20.CrossRefGoogle Scholar - Becker, G.S., Grossman, M., Murphy, K.M. (1991). Rational addiction and the effect of price on consumption.
*American Economic Review*,*81*(2), 237–241.Google Scholar - Becker, G.S., & Murphy, K.M. (1988). A theory of rational addiction.
*Journal of Political Economy*,*96*(4), 675–700.CrossRefGoogle Scholar - Bertrand, M., Duflo, E., Mullainathan, S. (2004). How much should we trust Differences-In-Differences estimates?.
*The Quarterly Journal of Economics*,*119*(1), 249–275.CrossRefGoogle Scholar - Blattberg, R.C., Briesch, R., Fox, E.J. (1995). How promotions work.
*Marketing Science*,*14*(3), G122–G132.CrossRefGoogle Scholar - Bolton, R.N. (1989). The relationship between market characteristics and promotional price elasticities.
*Marketing Science*,*8*, 153–159.CrossRefGoogle Scholar - Boulding, W., Lee, E., Staelin, R. (1995). Mastering the mix: do advertising, promotion and sales force activities lead to differentiation.
*Journal of Marketing Research*,*31*(2), 159–172.CrossRefGoogle Scholar - Briesch, R.A., Krishnamurthi, L., Mazumdar, T., Raj, S.P. (1997). A comparative analysis of reference price models.
*Journal of Consumer Research*,*24*(2), 202–214.CrossRefGoogle Scholar - Bronnenberg, B.J., Kim, J.B., Mela, C.F. (2016). Zooming in on choice: How do consumers search for cameras online?.
*Marketing Science*,*35*(5), 693–712.CrossRefGoogle Scholar - Cabral, L.M., & Villas-Boas, M. (2005). Bertrand supertraps.
*Management Science*,*51*(4), 599–613.CrossRefGoogle Scholar - Cameron, A.C., Gelbach, J.B., Miller, D.L. (2008). Bootstrap-based improvements for inference with clustered errors.
*Review of Economics and Statistics*,*90*(3), 414–427.CrossRefGoogle Scholar - Cameron, A.C., & Miller, D.L. (2015). A practitioner’s guide to cluster-robust inference.
*Journal of Human Resources*,*50*, 317–372.CrossRefGoogle Scholar - Chan, T., Narasimhan, C., Zhang, Q. (2008). Decomposing promotional effects with a dynamic structural model of flexible consumption.
*Journal of Marketing Research*,*45*(4), 487–498.CrossRefGoogle Scholar - Choi, M., Dai, A.Y., Kim, K. (2018). Consumer search and price competition.
*Econometrica*,*86*(4), 1257–1281.CrossRefGoogle Scholar - Davis, S.J., Inman, J., McAlister, L. (1992). Promotion has a Negative Effect on Brand Evaluations-Or Does it? Additional Disconforming Evidence.
*Journal of Marketing Research*,*29*(1), 143–148.Google Scholar - Dodson, J.A., Tybout, A.M., Sternthal, B. (1978). Impact of deals and deal retraction on brand switching.
*Journal of Marketing Research*,*15*(1), 71–81.CrossRefGoogle Scholar - Dube, J. -P., Hitsch, G.J., Rossi, P.E. (2010). State dependence and alternative explanations for consumer inertia.
*The RAND Journal of Economics*,*41*(3), 417–445.CrossRefGoogle Scholar - Ehrenberg, A.S.C., Hammond, K., Goodhardt, G.J. (1994). The After-Effects of Price-Related consumer promotions.
*Journal of Advertising Research*,*34*(4), 11–21.Google Scholar - Erdem, T., Imai, S., Keane, M.P. (2003). Brand and quantity choice dynamics under price uncertainty.
*Quantitative Marketing and Economics*,*1*(1), 5–64.CrossRefGoogle Scholar - Erdem, T., Keane, M.P., Sun, B. (2008). A dynamic model of brand choice when price and advertising signal product quality.
*Marketing Science*,*27*(6), 1111–1125.CrossRefGoogle Scholar - Freimer, M., & Horsky, D. (2008). Try it, you will like it - Does consumer learning lead to competitive price promotions?.
*Marketing Science*,*27*(5), 796–810.CrossRefGoogle Scholar - Gedenk, K., & Neslin, S.A. (1999). The role of retail promotion in determining future brand loyalty: Its effect on purchase event feedback.
*Journal of Retailing*,*75*(4), 433–459.CrossRefGoogle Scholar - Gedenk, K., Neslin, S.A., Ailawadi, K.L. (2010).
*Sales Promotion in: Retailing in the 21st Century: Current and Future Trends*. Berlin: Springer-Verlag Eds.Google Scholar - Guadagni, P.M., & Little, J.D. (1983). A logit model of brand choice calibrated on scanner data.
*Marketing Science*,*2*(3), 203–238.CrossRefGoogle Scholar - Hauser, J.R., & Wernerfelt, B. (1990). An evaluation cost model of consideration sets.
*Journal of Consumer Research*,*16*(4), 393–408.CrossRefGoogle Scholar - Honka, E. (2014). Quantifying search and switching costs in the US auto insurance industry.
*The RAND Journal of Economics*,*45*(4), 847–884.CrossRefGoogle Scholar - Honka, E., & Chintagunta, P. (2017). Simultaneous or Sequential? Search Strategies in the U.S. Auto Insurance Industry.
*Marketing Science*,*36*(1), 21–42.CrossRefGoogle Scholar - Imbens, G. (2011). Experimental design for unit and cluster randomized trials, 3ie, International Initiative for Impact Evaluation.Google Scholar
- Imbens, G., & Kolesar, M. (2015). Robust Standard Errors in Small Samples: Some Practical Advice. Working Paper.Google Scholar
- Imbens, G.W., & Rubin, D.B. (2015).
*Causal inference in statistics, social, and biomedical sciences*. Cambridge: Cambridge University Press.CrossRefGoogle Scholar - Jedidi, K., Mela, C.F., Gupta, S. (1999). Managing advertising and promotion for long-run profitability.
*Marketing Science*,*18*(1), 1–22.CrossRefGoogle Scholar - Jones, J.M., & Zufryden, F.S. (1980). Adding explanatory variables to a consumer purchase behavior model: an exploratory study.
*Journal of Marketing Research*,*17*(3), 47–53.CrossRefGoogle Scholar - Ke, T.T., Shen, Z. -J. M., Villas-Boas, J.M. (2016). Search for information on multiple products.
*Management Science*,*62*(12), 3576–3603.CrossRefGoogle Scholar - Kehoe, P., & Midrigan, V. (2015). Prices are sticky after all.
*Journal of Monetary Economics*,*75*, 35–53.CrossRefGoogle Scholar - Kim, J.B., Albuquerque, P., Bronnenberg, B.J. (2010). Online demand under limited consumer search.
*Marketing Science*,*29*(6), 1001–1023.CrossRefGoogle Scholar - Kopalle, P.K., Mela, C.F., Marsh, L. (1999). The dynamic effect of discounting on sales: Empirical analysis and normative pricing implications.
*Marketing Science*,*18*(3), 317–332.CrossRefGoogle Scholar - Lal, R., & Matutes, C. (1994). Retail pricing and advertising strategies.
*Journal of Business*,*67*(3), 345–370.CrossRefGoogle Scholar - McFadden, D. (1989). A method of simulated moments for estimation of discrete response models without numerical integration.
*Econometrica*,*57*(5), 995–1026.CrossRefGoogle Scholar - Mela, C.F., Gupta, S., Lehmann, D.R. (1997). The long-term impact of promotion and advertising on consumer brand choice.
*Journal of Marketing Research*,*34*(2), 248–261.CrossRefGoogle Scholar - Narasimhan, C., Neslin, S.A., Sen, S.K. (1996). Promotional elasticities and category characteristics.
*Journal of Marketing*,*60*(2), 17–30.CrossRefGoogle Scholar - Neslin, S.A., & Shoemaker, R.W. (1989). An alternative explanation for lower repeat rates after promotion purchases.
*Journal of Marketing Research*,*26*(2), 205–213.CrossRefGoogle Scholar - Neslin, S.A., & Van Heerde, H.J. (2009). Promotion dynamics.
*Foundations and Trends in Marketing*,*3*(4), 177–268.CrossRefGoogle Scholar - Pollak, R.A. (1970). Habit formation and dynamic demand functions.
*Journal of Political Economy*,*78*(4, Part 1), 745–763.CrossRefGoogle Scholar - Raju, J.S. (1992). The effect of price promotions on variability in product category sales.
*Marketing Science*,*11*(3), 207–220.CrossRefGoogle Scholar - Rubin, D.B. (1973). Matching to remove bias in observational studies.
*Biometrics*,*29*, 159–183.CrossRefGoogle Scholar - Rubin, D.B. (1979). Using multivariate matched sampling and regression adjustment to control bias in observational studies.
*Journal of the American Statistical Association*,*74*(366), 318–328.CrossRefGoogle Scholar - Scott, C.A. (1976). The effects of trial and incentives on repeat purchase behavior.
*Journal of Marketing Research*,*13*(1), 263–269.CrossRefGoogle Scholar - Seiler, S. (2013). The impact of search costs on consumer behavior: a dynamic approach.
*Quantitative Marketing and Economics*,*11*(2), 155–203.CrossRefGoogle Scholar - Seiler, S., & Pinna, F. (2017). Estimating search benefits from Path-Tracking data: Measurement and determinants, Marketing Science, Forthcoming.Google Scholar
- Shoemaker, R.W., & Shoaf, R.F. (1977). Repeat rates of deal purchases.
*Journal of Advertising Research*,*17*(2), 47–53.Google Scholar - Shugan, S.M. (1980). The cost of thinking.
*Journal of Consumer Research*,*7*(2), 99–111.CrossRefGoogle Scholar - Spinnewyn, F. (1981). Rational habit formation.
*European Economic Review*,*15*(1), 91–109.CrossRefGoogle Scholar - Train, K.E. (2009).
*Discrete choice methods with simulation*. Cambridge: Cambridge University Press.CrossRefGoogle Scholar - Tuchman, A., Nair, H., Gardete, P.M. (2017). Complementarities in consumption and the consumer demand for advertising, Working Paper.Google Scholar
- Villas-Boas, S.B., & Villas-Boas, J.M. (2008). Learning, forgetting, and sales.
*Management Science*,*54*(11), 1951–1960.CrossRefGoogle Scholar - Vuong, Q.H. (1989). Likelihood ratio tests for model selection and non-nested hypotheses.
*Econometrica*,*57*(2), 307–333.CrossRefGoogle Scholar - Weitzman, M.L. (1979). Optimal search for the best alternative.
*Econometrica*,*47*(3), 641–654.CrossRefGoogle Scholar - Zenor, M.J., Bronnenberg, B.J., McAlister, L. (1998). The impact of marketing policy on promotional price elasticities and baseline sales.
*Journal of Retailing and Consumer Services*,*5*(1), 25–32.CrossRefGoogle Scholar - Zou, D. (2014). Intertemporal pricing of new products, Incentivizing Consumer Learning and Inertia, Working Paper.Google Scholar
- Zubizarreta, J.R. (2012). Using mixed integer programming for matching in an observational study of kidney failure after surgery.
*Journal of the American Statistical Association*,*107*(500), 1360–1371.CrossRefGoogle Scholar