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The Dynamic Effect of Discounting on Sales: Empirical Analysis and Normative Pricing Implications

Author

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  • Praveen K. Kopalle

    (Amos Tuck School of Business Administration, Dartmouth College, Hanover, New Hampshire 03755)

  • Carl F. Mela

    (Fugua School of Business, Duke University, Durham, North Carolina, 27708)

  • Lawrence Marsh

    (Department of Economics, University of Notre Dame, Notre Dame, Indiana 46556)

Abstract

Baseline sales measure what retail sales would be in the absence of a promotion (Abraham and Lodish 1993), and models that measure baseline sales are widely used by managers to assess the profitability of promotions (Bucklin and Gupta 1999–this issue). Estimates of baseline sales and promotional response are typically independent of past promotional activity, even though there is evidence to suggest that increased discounting reduces off-promotion sales and increases the percentage of purchases made on deal (e.g., Krishna 1994). As a result, models that do not consider dynamic promotional effects can mislead managers to overpromote. Given the widespread use of “static” models to evaluate the efficacy of promotions, it is particularly desirable to calibrate a dynamic brand sales model and use it to establish an optimal course of action. Accordingly, we develop a descriptive dynamic brand sales model and use it to determine normative price promotion strategies. Our descriptive approach consists of estimating a varying-parameter sales response model. Letting model parameters vary with past discounting activity accommodates the possibility that market response changes with firms' discounting policies. In the normative model, we use the estimates obtained in the descriptive model to determine optimal retailer and manufacturer prices over time. The results of the descriptive model indicate that promotions have positive contemporaneous effects on sales accompanied by negative future effects on baseline sales. The results of the normative model suggest that the higher-share brands in our data tend to overpromote while the lower-share brands do not promote frequently enough. We project that the use of our model could improve manufacturers' profits by as much as 7% to 31%. More generally, the normative results indicate that i) if deals become more effective in the current period, i.e., if consumers are more price sensitive, promotions should be used more frequently; and ii) as the negative dynamic effect of discounts on sales increases, the optimal level of discounting should go down. Without our approach, it would be difficult to make this trade-off exact. Finally, we demonstrate that these dynamic effects provide another perspective to the marketing literature regarding the existence of promotions.

Suggested Citation

  • Praveen K. Kopalle & Carl F. Mela & Lawrence Marsh, 1999. "The Dynamic Effect of Discounting on Sales: Empirical Analysis and Normative Pricing Implications," Marketing Science, INFORMS, vol. 18(3), pages 317-332.
  • Handle: RePEc:inm:ormksc:v:18:y:1999:i:3:p:317-332
    DOI: 10.1287/mksc.18.3.317
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    References listed on IDEAS

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    1. Kamel Jedidi & Carl F. Mela & Sunil Gupta, 1999. "Managing Advertising and Promotion for Long-Run Profitability," Marketing Science, INFORMS, vol. 18(1), pages 1-22.
    2. Robert C. Blattberg & Richard Briesch & Edward J. Fox, 1995. "How Promotions Work," Marketing Science, INFORMS, vol. 14(3_supplem), pages 122-132.
    3. Timothy W. McGuire & Richard Staelin, 1983. "An Industry Equilibrium Analysis of Downstream Vertical Integration," Marketing Science, INFORMS, vol. 2(2), pages 161-191.
    4. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    5. Keane, Michael, 1997. "Current Issues in Discrete Choice Modeling," MPRA Paper 52515, University Library of Munich, Germany.
    6. David Besanko & Sachin Gupta & Dipak Jain, 1998. "Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework," Management Science, INFORMS, vol. 44(11-Part-1), pages 1533-1547, November.
    7. Magid M. Abraham & Leonard M. Lodish, 1993. "An Implemented System for Improving Promotion Productivity Using Store Scanner Data," Marketing Science, INFORMS, vol. 12(3), pages 248-269.
    8. Ruth N. Bolton, 1989. "The Relationship Between Market Characteristics and Promotional Price Elasticities," Marketing Science, INFORMS, vol. 8(2), pages 153-169.
    9. David R. Bell & Jeongwen Chiang & V. Padmanabhan, 1999. "The Decomposition of Promotional Response: An Empirical Generalization," Marketing Science, INFORMS, vol. 18(4), pages 504-526.
    10. Ram C. Rao, 1991. "Pricing and Promotions in Asymmetric Duopolies," Marketing Science, INFORMS, vol. 10(2), pages 131-144.
    11. Scott A. Neslin & Caroline Henderson & John Quelch, 1985. "Consumer Promotions and the Acceleration of Product Purchases," Marketing Science, INFORMS, vol. 4(2), pages 147-165.
    12. Jorge M. Silva-Risso & Randolph E. Bucklin & Donald G. Morrison, 1999. "A Decision Support System for Planning Manufacturers' Sales Promotion Calendars," Marketing Science, INFORMS, vol. 18(3), pages 274-300.
    13. Eric A. Greenleaf, 1995. "The Impact of Reference Price Effects on the Profitability of Price Promotions," Marketing Science, INFORMS, vol. 14(1), pages 82-104.
    14. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    15. Eunkyu Lee & Richard Staelin, 1997. "Vertical Strategic Interaction: Implications for Channel Pricing Strategy," Marketing Science, INFORMS, vol. 16(3), pages 185-207.
    16. Rajiv Lal, 1990. "Price Promotions: Limiting Competitive Encroachment," Marketing Science, INFORMS, vol. 9(3), pages 247-262.
    17. Robert C. Blattberg & Kenneth J. Wisniewski, 1989. "Price-Induced Patterns of Competition," Marketing Science, INFORMS, vol. 8(4), pages 291-309.
    18. Magid M. Abraham & Leonard M. Lodish, 1987. "Promoter: An Automated Promotion Evaluation System," Marketing Science, INFORMS, vol. 6(2), pages 101-123.
    19. Gerard J. Tellis & Fred S. Zufryden, 1995. "Tackling the Retailer Decision Maze: Which Brands to Discount, How Much, When and Why?," Marketing Science, INFORMS, vol. 14(3), pages 271-299.
    20. Peter S. Fader & James M. Lattin & John D. C. Little, 1992. "Estimating Nonlinear Parameters in the Multinomial Logit Model," Marketing Science, INFORMS, vol. 11(4), pages 372-385.
    21. Gurumurthy Kalyanaram & Russell S. Winer, 1995. "Empirical Generalizations from Reference Price Research," Marketing Science, INFORMS, vol. 14(3_supplem), pages 161-169.
    22. Abel P. Jeuland & Steven M. Shugan, 1988. "Note—Channel of Distribution Profits When Channel Members Form Conjectures," Marketing Science, INFORMS, vol. 7(2), pages 202-210.
    23. Kadiyali, Vrinda & Vilcassim, Naufel J & Chintagunta, Pradeep K, 1996. "Empirical Analysis of Competitive Product Line Pricing Decisions: Lead, Follow, or Move Together?," The Journal of Business, University of Chicago Press, vol. 69(4), pages 459-487, October.
    24. Aradhna Krishna, 1994. "The Impact of Dealing Patterns on Purchase Behavior," Marketing Science, INFORMS, vol. 13(4), pages 351-373.
    25. Scott A. Neslin & Stephen G. Powell & Linda Schneider Stone, 1995. "The Effects of Retailer and Consumer Response on Optimal Manufacturer Advertising and Trade Promotion Strategies," Management Science, INFORMS, vol. 41(5), pages 749-766, May.
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