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—Marketing-Mix Recommendations to Manage Value Growth at P&G Asia-Pacific

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Author Info

  • V. Kumar

    ()
    (J. Mack Robinson College of Business, Georgia State University, Altanta, Georgia 30303)

  • Jia Fan

    ()
    (J. Mack Robinson College of Business, Georgia State University, Altanta, Georgia 30303)

  • Rohit Gulati

    ()
    (Proctor & Gamble Asia-Pacific, Pte Ltd., Singapore 307684)

  • P. Venkat

    ()
    (Proctor & Gamble Asia-Pacific, Pte Ltd., Singapore 307684)

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    Abstract

    Procter & Gamble (P&G) Asia-Pacific is interested in managing value growth. Only after fully understanding the true effects of the marketing-mix variables can P&G managers make strategic decisions answering questions such as the following: (1) Are the P&G brands in the detergent market inelastic or elastic with respect to price? How has the price elasticity changed over time? Can P&G increase the price of its brands to gain value growth? (2) What are the price, distribution, and sizing combinations needed to achieve the desirable value growth? (3) How can P&G gain market share from its competitors without cannibalizing its own brands? P&G Asia-Pacific approached us to develop a value growth framework to answer these questions. To generate the answers for the above questions, we develop a three-step weighted random coefficient estimator that captures the heterogeneity across cross sections (different stock-keeping units and states) and the endogeneity of distribution. Based on the parameter estimates, we provide strategic recommendations to P&G for a field test to validate our suggestions. We developed a simulator for P&G managers so that they can generate appropriate marketing-mix strategies for achieving the desired value growth. As a result, P&G gained over $39 million in value growth over a one-year period by implementing the recommendations from our modeling approach.

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    File URL: http://dx.doi.org/10.1287/mksc.1080.0477
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    Bibliographic Info

    Article provided by INFORMS in its journal Marketing Science.

    Volume (Year): 28 (2009)
    Issue (Month): 4 (07-08)
    Pages: 645-655

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    Handle: RePEc:inm:ormksc:v:28:y:2009:i:4:p:645-655

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    Related research

    Keywords: marketing mix; price elasticity; distribution; random coefficient model; system of equations; sales value; revenue; sales volume;

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