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A Prelaunch Diffusion Model for Evaluating Market Defense Strategies

Author

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  • John H. Roberts

    (Australian Graduate School of Management, University of New South Wales, Sydney, NSW 2052, Australia, and London Business School, Regents Park, London NW1 4SA, United Kingdom)

  • Charles J. Nelson

    (Foreseechange Pty Limited, 6 Paterson Street, Brunswick VIC 3056, Australia)

  • Pamela D. Morrison

    (School of Marketing, University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

This paper describes the development and application of a marketing model to help set an incumbent's defensive marketing strategy prior to a new competitor's launch. The management problem addressed is to assess the market share impact of a new entrant in the residential Australian long distance telephone call market and determine the factors that would influence its dynamics and ultimate market appeal. The paper uses probability flow models to provide a framework to generate forecasts and assess the determinants of share loss. We develop models at two levels of complexity to give both simple, robust forecasts and more detailed diagnostic analysis of the effect of marketing actions. The models are calibrated prior to the new entrant's launch, enabling preemptive marketing strategies to be put in place by the defending company. The equilibrium level of consideration of the new entrant was driven by respondents' strength of relationship with the defender and inertia, while trial was more price-based. Continued use of the defender depends on both service factors and price. The rate at which share loss eventuates is negatively related to the defender's perceived responsiveness, saving money being the only reason to switch, and risk aversion. Prelaunch model forecasts, validated six months after launch using both aggregate monthly sales data and detailed tracking surveys, are shown to closely follow the actual evolution of the market. The paper provides a closed-form multistate model of the new entrant's diffusion, a methodology for the prelaunch calibration of dynamic models in practice, and insights into defensive strategies for existing companies facing new entrants.

Suggested Citation

  • John H. Roberts & Charles J. Nelson & Pamela D. Morrison, 2005. "A Prelaunch Diffusion Model for Evaluating Market Defense Strategies," Marketing Science, INFORMS, vol. 24(1), pages 150-164, August.
  • Handle: RePEc:inm:ormksc:v:24:y:2005:i:1:p:150-164
    DOI: 10.1287/mksc.1040.0086
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    References listed on IDEAS

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    2. Polo, Yolanda & Sese, F. Javier & Verhoef, Peter C., 2011. "The Effect of Pricing and Advertising on Customer Retention in a Liberalizing Market," Journal of Interactive Marketing, Elsevier, vol. 25(4), pages 201-214.
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    6. Ashish Sinha & J. Jeffrey Inman & Yantao Wang & Joonwook Park & Gerard J. Tellis & Rajesh K. Chandy & Deborah MacInnis & Pattana Thaivanich, 2005. "Practice Prize Reports," Marketing Science, INFORMS, vol. 24(3), pages 351-366, September.
    7. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    8. Bridges, Eileen & Freytag, Per V., 2009. "When do firms invest in offensive and/or defensive marketing?," Journal of Business Research, Elsevier, vol. 62(7), pages 745-749, July.
    9. Lan Luo & P. K. Kannan & Brian T. Ratchford, 2007. "New Product Development Under Channel Acceptance," Marketing Science, INFORMS, vol. 26(2), pages 149-163, 03-04.
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    12. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
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    14. 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.

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