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Effective Marketing Science Applications: Insights from the ISMS-MSI Practice Prize Finalist Papers and Projects

Author

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  • Gary L. Lilien

    (Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • John H. Roberts

    (College of Business and Economics, Australian National University, Canberra, Australian Capital Territory 0200, Australia; and London Business School, London NW1 4SA, United Kingdom)

  • Venkatesh Shankar

    (Mays Business School, Texas A&M University, College Station, Texas 77843)

Abstract

From 2003 to 2012, the ISMS-MSI Practice Prize/Award competition has documented 25 impactful projects, with associated papers appearing in Marketing Science . This article reviews these papers and projects, examines their influence on the relevant organizations, and provides a perspective on the diffusion and impact of marketing science models within the organizations. We base our analysis on three sources of data---the articles, authors' responses to a survey, and in-depth interviews with the authors. We draw some conclusions about how marketing science models can create more impact without losing academic rigor while maintaining strong relevance to practice. We find that the application and diffusion of marketing science models are not restricted to the well-known choice models, conjoint analysis, mapping, and promotional analysis---there are very effective applications across a wide range of managerial problems using an array of marketing science techniques. There is no one successful approach, and although some factors are correlated with impactful marketing science models, there are a number of pathways by which a project can add value to its client organization. Simpler, easier-to-use models that offer robust and improved results can have a stronger impact than academically sophisticated models can. Organizational buy-in is critical and can be achieved through recognizing high-level champions, holding in-house presentations and dialogues, doing pilot assignments, involving multidepartment personnel, and speaking the same language as the influential executives. And we find that intermediaries often, but not always, play a key role in the transportability and diffusion of models across organizations. Although these applications are impressive and reflect profitable academic--practitioner partnerships, changes in the knowledge base and reward systems for academics, intermediaries, and practitioners are required for marketing science approaches to realize their potential impact on a much larger scale than the highly selective sample that we have been able to analyze.

Suggested Citation

  • Gary L. Lilien & John H. Roberts & Venkatesh Shankar, 2013. "Effective Marketing Science Applications: Insights from the ISMS-MSI Practice Prize Finalist Papers and Projects," Marketing Science, INFORMS, vol. 32(2), pages 229-245, March.
  • Handle: RePEc:inm:ormksc:v:32:y:2013:i:2:p:229-245
    DOI: 10.1287/mksc.1120.0756
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    References listed on IDEAS

    as
    1. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    2. V. Kumar & Rajkumar Venkatesan & Tim Bohling & Denise Beckmann, 2008. "—The Power of CLV: Managing Customer Lifetime Value at IBM," Marketing Science, INFORMS, vol. 27(4), pages 585-599, 07-08.
    3. Germann, Frank & Lilien, Gary L. & Rangaswamy, Arvind, 2013. "Performance implications of deploying marketing analytics," International Journal of Research in Marketing, Elsevier, vol. 30(2), pages 114-128.
    4. Venkatesh Shankar & Pablo Azar & Matthew Fuller, 2008. "—: A Multicategory Brand Equity Model and Its Application at Allstate," Marketing Science, INFORMS, vol. 27(4), pages 567-584, 07-08.
    5. Roberts, John H., 2010. "Has research in marketing lost its way?," Australasian marketing journal, Elsevier, vol. 18(3), pages 161-164.
    6. Thorsten Wiesel & Koen Pauwels & Joep Arts, 2011. "Practice Prize Paper --Marketing's Profit Impact: Quantifying Online and Off-line Funnel Progression," Marketing Science, INFORMS, vol. 30(4), pages 604-611, July.
    7. Berend Wierenga & Gerrit H. Van Bruggen & Richard Staelin, 1999. "The Success of Marketing Management Support Systems," Marketing Science, INFORMS, vol. 18(3), pages 196-207.
    8. John D. C. Little, 1970. "Models and Managers: The Concept of a Decision Calculus," Management Science, INFORMS, vol. 16(8), pages 466-485, April.
    9. William Boulding & Richard Staelin, 1990. "Environment, Market Share, and Market Power," Management Science, INFORMS, vol. 36(10), pages 1160-1177, October.
    10. Giuliano Tirenni & Abderrahim Labbi & Cesar Berrospi & André Elisseeff & Timir Bhose & Kari Pauro & Seppo Pöyhönen, 2007. "—Customer Equity and Lifetime Management (CELM) Finnair Case Study," Marketing Science, INFORMS, vol. 26(4), pages 553-565, 07-08.
    11. John D. C. Little, 2004. "Models and Managers: The Concept of a Decision Calculus," Management Science, INFORMS, vol. 50(12_supple), pages 1841-1853, December.
    12. Andris A. Zoltners & Prabhakant Sinha, 2005. "The 2004 ISMS Practice Prize Winner—Sales Territory Design: Thirty Years of Modeling and Implementation," Marketing Science, INFORMS, vol. 24(3), pages 313-331, September.
    13. Leeflang, P.S.H. & Wittink, Dick R., 2000. "Building models for marketing decisions: past, present and future," Research Report 00F20, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    14. Jie Du & Lili Xie & Stephan Schroeder, 2009. "—PIN Optimal Distribution of Auction Vehicles System: Applying Price Forecasting, Elasticity Estimation, and Genetic Algorithms to Used-Vehicle Distribution," Marketing Science, INFORMS, vol. 28(4), pages 637-644, 07-08.
    15. Jorge Silva-Risso & Irina Ionova, 2008. "—A Nested Logit Model of Product and Transaction-Type Choice for Planning Automakers' Pricing and Promotions," Marketing Science, INFORMS, vol. 27(4), pages 545-566, 07-08.
    16. Suresh Divakar & Brian T. Ratchford & Venkatesh Shankar, 2005. "Practice Prize Article—: A Multichannel, Multiregion Sales Forecasting Model and Decision Support System for Consumer Packaged Goods," Marketing Science, INFORMS, vol. 24(3), pages 334-350, July.
    17. Kusum L. Ailawadi & Bari A. Harlam & Jacques César & David Trounce, 2007. "Practice Prize Report—Quantifying and Improving Promotion Effectiveness at CVS," Marketing Science, INFORMS, vol. 26(4), pages 566-575, 07-08.
    18. Martin Natter & Thomas Reutterer & Andreas Mild & Alfred Taudes, 2007. "—An Assortmentwide Decision-Support System for Dynamic Pricing and Promotion Planning in DIY Retailing," Marketing Science, INFORMS, vol. 26(4), pages 576-583, 07-08.
    19. Leonard M. Lodish, 2001. "Building Marketing Models that Make Money," Interfaces, INFORMS, vol. 31(3_supplem), pages 45-55, June.
    20. P. K. Kannan & Barbara Kline Pope & Sanjay Jain, 2009. "—Pricing Digital Content Product Lines: A Model and Application for the National Academies Press," Marketing Science, INFORMS, vol. 28(4), pages 620-636, 07-08.
    21. repec:dgr:rugsom:00f20 is not listed on IDEAS
    22. Marc Fischer & Sönke Albers & Nils Wagner & Monika Frie, 2011. "Practice Prize Winner --Dynamic Marketing Budget Allocation Across Countries, Products, and Marketing Activities," Marketing Science, INFORMS, vol. 30(4), pages 568-585, July.
    23. Ashish Sinha & Anna Sahgal & Sharat K. Mathur, 2013. "Practice Prize Paper ---Category Optimizer: A Dynamic-Assortment, New-Product-Introduction, Mix-Optimization, and Demand-Planning System," Marketing Science, INFORMS, vol. 32(2), pages 221-228, March.
    24. Ralf Elsner & Manfred Krafft & Arnd Huchzermeier, 2004. "The 2003 ISMS Practice Prize Winner: Optimizing Rhenania's Direct Marketing Business Through Dynamic Multilevel Modeling (DMLM) in a Multicatalog-Brand Environment," Marketing Science, INFORMS, vol. 23(2), pages 192-206, June.
    25. V. Kumar & Denish Shah, 2011. "Practice Prize Paper --Uncovering Implicit Consumer Needs for Determining Explicit Product Positioning: Growing Prudential Annuities' Variable Annuity Sales," Marketing Science, INFORMS, vol. 30(4), pages 595-603, July.
    26. Albers, Sönke, 2012. "Optimizable and implementable aggregate response modeling for marketing decision support," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 111-122.
    27. V. Kumar & Jia Fan & Rohit Gulati & P. Venkat, 2009. "—Marketing-Mix Recommendations to Manage Value Growth at P&G Asia-Pacific," Marketing Science, INFORMS, vol. 28(4), pages 645-655, 07-08.
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    3. Abhishek Borah & Xin (Shane) Wang & Jun Hyun (Joseph) Ryoo, 2018. "Understanding Influence of Marketing Thought on Practice: an Analysis of Business Journals Using Textual and Latent Dirichlet Allocation (LDA) Analysis," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(3), pages 146-161, December.
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    5. Lan Luo & Koen Pauwels, 2023. "Practice Prize Report: The 2020 and 2022 ISMS Gary Lilien Practice Prize Competition," Marketing Science, INFORMS, vol. 42(1), pages 6-10, January.
    6. Frank Germann & Gary L. Lilien & Christine Moorman & Lars Fiedler & Till Groβmaβ, 2021. "Driving Customer Analytics From the Top," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 43-61, October.
    7. 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.
    8. John H. Roberts, 2018. "Practice Prize Report: The 2016 ISMS Gary Lilien Practice Prize Competition," Marketing Science, INFORMS, vol. 37(5), pages 685-687, September.
    9. Frank Germann & Gary L. Lilien & Christine Moorman & Lars Fiedler & Till Groβmaβ, 2020. "Driving Customer Analytics From the Top," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 7(3), pages 43-61, October.
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