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Consumer Attitude Metrics for Guiding Marketing Mix Decisions

Author

Listed:
  • Dominique M. Hanssens

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095)

  • Koen H. Pauwels

    (Özyeğin University, Istanbul, 34794 Turkey)

  • Shuba Srinivasan

    (Boston University School of Management, Boston University, Boston, Massachusetts 02215)

  • Marc Vanhuele

    (HEC Paris, 78351 Jouy-en-Josas, France)

  • Gokhan Yildirim

    (Management School, Lancaster University, Bailrigg, Lancaster LA1 4YX, United Kingdom)

Abstract

Marketing managers often use consumer attitude metrics such as awareness, consideration, and preference as performance indicators because they represent their brand's health and are readily connected to marketing activity. However, this does not mean that financially focused executives know how such metrics translate into sales performance, which would allow them to make beneficial marketing mix decisions. We propose four criteria---potential, responsiveness, stickiness, and sales conversion---that determine the connection between marketing actions, attitudinal metrics, and sales outcomes.We test our approach with a rich data set of four-weekly marketing actions, attitude metrics, and sales for several consumer brands in four categories over a seven-year period. The results quantify how marketing actions affect sales performance through their differential impact on attitudinal metrics, as captured by our proposed criteria. We find that marketing--attitude and attitude--sales relationships are predominantly stable over time but differ substantially across brands and product categories. We also establish that combining marketing and attitudinal metrics criteria improves the prediction of brand sales performance, often substantially so. Based on these insights, we provide specific recommendations on improving the marketing mix for different brands, and we validate them in a holdout sample. For managers and researchers alike, our criteria offer a verifiable explanation for differences in marketing elasticities and an actionable connection between marketing and financial performance metrics.

Suggested Citation

  • Dominique M. Hanssens & Koen H. Pauwels & Shuba Srinivasan & Marc Vanhuele & Gokhan Yildirim, 2014. "Consumer Attitude Metrics for Guiding Marketing Mix Decisions," Marketing Science, INFORMS, vol. 33(4), pages 534-550, July.
  • Handle: RePEc:inm:ormksc:v:33:y:2014:i:4:p:534-550
    DOI: 10.1287/mksc.2013.0841
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    References listed on IDEAS

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    1. Franses, Ph.H.B.F. & Vriens, M., 2004. "Advertising effects on awareness, consideration and brand choice using tracking data," ERIM Report Series Research in Management ERS-2004-028-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.
    2. Batra, Rajeev & Vanhonacker, Wilfried R., 1988. "Falsifying laboratory results through field tests: A time-series methodology and some results," Journal of Business Research, Elsevier, vol. 16(4), pages 281-300, June.
    3. Kardes, Frank R, 1986. "Effects of Initial Product Judgments on Subsequent Memory-Based Judgments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 13(1), pages 1-11, June.
    4. Belch, George E, 1982. "The Effects of Television Commercial Repetition on Cognitive Response and Message Acceptance," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 9(1), pages 56-65, June.
    5. Burke, Raymond R & Srull, Thomas K, 1988. "Competitive Interference and Consumer Memory for Advertising," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(1), pages 55-68, June.
    6. Simmons, Carolyn J & Bickart, Barbara A & Lynch, John G, Jr, 1993. "Capturing and Creating Public Opinion in Survey Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 20(2), pages 316-329, September.
    7. Richard P. Bagozzi & Alvin J. Silk, 1983. "Recall, Recognition, and the Measurement of Memory for Print Advertisements," Marketing Science, INFORMS, vol. 2(2), pages 95-134.
    8. Peter, J Paul & Tarpey, Lawrence X, Sr, 1975. "A Comparative Analysis of Three Consumer Decision Strategies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(1), pages 29-37, June.
    9. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    10. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    11. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    12. Marc Vanhuele & Shuba Srinivasan & Koen Pauwels, 2010. "Mindset Metrics in Market Response Models: An Integrative Approach," Post-Print hal-00528411, HAL.
    13. Kevin Lane Keller & Donald R. Lehmann, 2006. "Brands and Branding: Research Findings and Future Priorities," Marketing Science, INFORMS, vol. 25(6), pages 740-759, 11-12.
    14. Pauwels, Koen & Erguncu, Selin & Yildirim, Gokhan, 2013. "Winning hearts, minds and sales: How marketing communication enters the purchase process in emerging and mature markets," International Journal of Research in Marketing, Elsevier, vol. 30(1), pages 57-68.
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