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A Logit Model of Brand Choice Calibrated on Scanner Data

Author

Listed:
  • Peter M. Guadagni

    (Bonanza Street Books, Walnut Creek, California 94596)

  • John D. C. Little

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142)

Abstract

A multinomial logit model of brand choice, calibrated on 32 weeks of purchases of regular ground coffee by 100 households, shows high statistical significance for the explanatory variables of brand loyalty, size loyalty, presence/absence of store promotion, regular shelf price and promotional price cut. The model is parsimonious in that the coefficients of these variables are modeled to be the same for all coffee brand-sizes. The calibrated model predicts remarkably well the share of purchases by brand-size in a hold-out sample of 100 households over the 32-week calibration period and a subsequent 20-week forecast period. The success of the model is attributed in part to the level of detail and completeness of the household panel data employed, which has been collected through optical scanning of the Universal Product Code in supermarkets. Three short-term market response measures are calculated from the model: regular (depromoted) price elasticity of share, percent increase in share for a promotion with a median price cut, and promotional price cut elasticity of share. Response varies across brand-sizes in a systematic way with large share brand-sizes showing less response in percentage terms but greater in absolute terms. On the basis of the model a quantitative picture emerges of groups of loyal customers who are relatively insensitive to marketing actions and a pool of switchers who are quite sensitive. This article was originally published in , Volume 2, Issue 3, pages 203–238, in 1983.

Suggested Citation

  • Peter M. Guadagni & John D. C. Little, 2008. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 27(1), pages 29-48, 01-02.
  • Handle: RePEc:inm:ormksc:v:27:y:2008:i:1:p:29-48
    DOI: 10.1287/mksc.1070.0331
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    References listed on IDEAS

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    1. John R. Hauser, 1978. "Testing the Accuracy, Usefulness, and Significance of Probabilistic Choice Models: An Information-Theoretic Approach," Operations Research, INFORMS, vol. 26(3), pages 406-421, June.
    2. Little, John D C & Shapiro, Jeremy F, 1980. "A Theory for Pricing Nonfeatured Products in Supermarkets," The Journal of Business, University of Chicago Press, vol. 53(3), pages 199-209, July.
    3. Theil, Henri, 1969. "A Multinomial Extension of the Linear Logit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(3), pages 251-259, October.
    4. Glen L. Urban & Philip L. Johnson & John R. Hauser, 1984. "Testing Competitive Market Structures," Marketing Science, INFORMS, vol. 3(2), pages 83-112.
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    5. Lusheng Shao, 2023. "Competitive multiproduct contracting under multinomial logit demand," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 379-396, February.
    6. Nakano, Satoshi & Kondo, Fumiyo N., 2018. "Customer segmentation with purchase channels and media touchpoints using single source panel data," Journal of Retailing and Consumer Services, Elsevier, vol. 41(C), pages 142-152.
    7. Melis, Kristina & Campo, Katia & Breugelmans, Els & Lamey, Lien, 2015. "The Impact of the Multi-channel Retail Mix on Online Store Choice: Does Online Experience Matter?," Journal of Retailing, Elsevier, vol. 91(2), pages 272-288.
    8. Lilien, Gary L., 2010. "Is academic marketing losing its way? Embrace intermediaries," Australasian marketing journal, Elsevier, vol. 18(3), pages 174-176.
    9. Julia Hoffmann & Julia Bronnmann, 2019. "Bottle size matters: Heterogeneity in the German carbonated soft drink market," Agribusiness, John Wiley & Sons, Ltd., vol. 35(4), pages 556-573, October.
    10. Hökelekli, Gizem & Lamey, Lien & Verboven, Frank, 2017. "Private label line proliferation and private label tier pricing: A new dimension of competition between private labels and national brands," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 39-52.
    11. Schwartz-Landsman, V., 2020. "A Chasm to Cross: From Research to Practice and Back," ERIM Inaugural Address Series Research in Management EIA 2020-081-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam..
    12. Hökelekli, Gizem & Lamey, Lien & Verboven, Frank, 2017. "The battle of traditional retailers versus discounters: The role of PL tiers," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 11-22.
    13. Roberts, John H. & Kayande, Ujwal & Stremersch, Stefan, 2014. "From academic research to marketing practice: Exploring the marketing science value chain," International Journal of Research in Marketing, Elsevier, vol. 31(2), pages 127-140.
    14. Samane Zare & Mahdi Asgari & Timothy Woods & Yuqing Zheng, 2020. "Consumer proximity and brand loyalty in craft soda marketing: A case study of Ale‐8‐One," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 522-541, October.
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