IDEAS home Printed from https://ideas.repec.org/a/now/fntmkt/1700000054.html
   My bibliography  Save this article

Modeling Dynamic Relations Among Marketing and Performance Metrics

Author

Listed:
  • Pauwels, Koen H.

Abstract

Marketing and performance data often include measures repeated over time. Time-series models are uniquely suited to capture the time dependence of both a criterion variable and predictor variables, and how they relate to each other over time. The objective of this monograph is to give you a foundation in these models and to enable you to apply them to your own research domain of interest. To this end, we will discuss both the underlying perspectives and differences between alternative models, and the practical issues with testing, model choice, model estimation and interpretation common in empirical research. This combination of marketing phenomena and modeling philosophy sets this work apart from previous treatments on the broader topic of econometics and time series analysis in marketing.

Suggested Citation

  • Pauwels, Koen H., 2018. "Modeling Dynamic Relations Among Marketing and Performance Metrics," Foundations and Trends(R) in Marketing, now publishers, vol. 11(4), pages 215-301, November.
    • Handle: RePEc:now:fntmkt:1700000054
    DOI: 10.1561/1700000054
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1561/1700000054
    Download Restriction: no
    File URL: https://libkey.io/10.1561/1700000054?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Takada, Hirokazu & Bass, Frank M., 1998. "Multiple Time Series Analysis of Competitive Marketing Behavior," Journal of Business Research, Elsevier, vol. 43(2), pages 97-107, October.
    2. Jan-Benedict E. M. Steenkamp & Vincent R. Nijs & Dominique M. Hanssens & Marnik G. Dekimpe, 2005. "Competitive Reactions to Advertising and Promotion Attacks," Marketing Science, INFORMS, vol. 24(1), pages 35-54, September.
    3. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    4. Zellner, Arnold & Palm, Franz, 1974. "Time series analysis and simultaneous equation econometric models," Journal of Econometrics, Elsevier, vol. 2(1), pages 17-54, May.
    5. Wiesel Thorsten & Skiera Bernd & Villanueva Julián, 2010. "My customers are better than yours! On Reporting Customer Equity," GfK Marketing Intelligence Review, Sciendo, vol. 2(1), pages 42-53, May.
    6. Harald Van Heerde & Kristiaan Helsen & Marnik G. Dekimpe, 2007. "The Impact of a Product-Harm Crisis on Marketing Effectiveness," Marketing Science, INFORMS, vol. 26(2), pages 230-245, 03-04.
    7. Marc Vanhuele & Shuba Srinivasan & Koen Pauwels, 2010. "Mindset Metrics in Market Response Models: An Integrative Approach," Post-Print hal-00528411, HAL.
    8. Ljungqvist, Lars & Uhlig, Harald, 1999. "On Consumption Bunching under Campbell-Cochrane Habit Formation," SSE/EFI Working Paper Series in Economics and Finance 337, Stockholm School of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Valter Afonso Vieira & Marcos Inácio Severo Almeida & Raj Agnihotri & Nôga Simões De Arruda Corrêa Silva & S. Arunachalam, 2019. "In pursuit of an effective B2B digital marketing strategy in an emerging market," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1085-1108, November.
    2. Simon J Blanchard & Jacob Goldenberg & Koen Pauwels & David A Schweidel, 2022. "Promoting Data Richness in Consumer Research: How to Develop and Evaluate Articles with Multiple Data Sources [The Critical Role of Methodological Pluralism for Policy-Relevant Empirical Marketing ," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(2), pages 359-372.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gijsenberg, Maarten J., 2014. "Going for gold: Investigating the (non)sense of increased advertising around major sports events," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 2-15.
    2. Kornelis, Marcel & Dekimpe, Marnik G. & Leeflang, Peter S.H., 2008. "Does competitive entry structurally change key marketing metrics?," International Journal of Research in Marketing, Elsevier, vol. 25(3), pages 173-182.
    3. Frison, Steffi & Dekimpe, Marnik G. & Croux, Christophe & De Maeyer, Peter, 2014. "Billboard and cinema advertising: Missed opportunity or spoiled arms?," International Journal of Research in Marketing, Elsevier, vol. 31(4), pages 425-433.
    4. Koen Pauwels & Dominique M. Hanssens, 2007. "Performance Regimes and Marketing Policy Shifts," Marketing Science, INFORMS, vol. 26(3), pages 293-311, 05-06.
    5. Ivan A. Guitart & Guillaume Hervet & Sarah Gelper, 2020. "Competitive advertising strategies for programmatic television," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 753-775, July.
    6. Ataman, B.M., 2007. "Managing brands," Other publications TiSEM 462dcbba-2ac1-46d1-a61c-f, Tilburg University, School of Economics and Management.
    7. Vincent R. Nijs & Shuba Srinivasan & Koen Pauwels, 2007. "Retail-Price Drivers and Retailer Profits," Marketing Science, INFORMS, vol. 26(4), pages 473-487, 07-08.
    8. 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.
    9. Szymanowski, Maciej & Gijsbrechts, Els, 2013. "Patterns in consumption-based learning about brand quality for consumer packaged goods," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 219-235.
    10. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    11. Valter Afonso Vieira & Marcos Inácio Severo Almeida & Raj Agnihotri & Nôga Simões De Arruda Corrêa Silva & S. Arunachalam, 2019. "In pursuit of an effective B2B digital marketing strategy in an emerging market," Journal of the Academy of Marketing Science, Springer, vol. 47(6), pages 1085-1108, November.
    12. Gijsenberg, Maarten & Verhoef, Pieter, 2018. "Moving Forward," Research Report 2018003-MARK, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    13. Harald J. van Heerde & Shuba Srinivasan & Marnik G. Dekimpe, 2010. "Estimating Cannibalization Rates for Pioneering Innovations," Marketing Science, INFORMS, vol. 29(6), pages 1024-1039, 11-12.
    14. M.G. Dekimpe & D.M. Hanssens, 2005. "Persistence Models and Marketing Strategy," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(5), pages 855-884.
    15. Csilla Horváth & Dennis Fok, 2013. "Moderating Factors of Immediate, Gross, and Net Cross-Brand Effects of Price Promotions," Marketing Science, INFORMS, vol. 32(1), pages 127-152, July.
    16. Charles Hugh Wilkie, Dean & Mirzaei, Abas & Pham, Ngoc & Johnson, Lester W., 2022. "Reassessing product line breadth effectiveness: The role of heterogeneity, moderation, and cumulative effects," Journal of Business Research, Elsevier, vol. 149(C), pages 434-447.
    17. Michael A. Wiles & Shailendra P. Jain & Saurabh Mishra & Charles Lindsey, 2010. "Stock Market Response to Regulatory Reports of Deceptive Advertising: The Moderating Effect of Omission Bias and Firm Reputation," Marketing Science, INFORMS, vol. 29(5), pages 828-845, 09-10.
    18. Reimer, Kerstin & Rutz, Oliver J. & Pauwels, Koen, 2014. "How Online Consumer Segments Differ in Long-term Marketing Effectiveness," Journal of Interactive Marketing, Elsevier, vol. 28(4), pages 271-284.
    19. Jung Ah Han & Elea McDonnell Feit & Shuba Srinivasan, 2020. "Can negative buzz increase awareness and purchase intent?," Marketing Letters, Springer, vol. 31(1), pages 89-104, March.

    More about this item

    Keywords

    time series models; multivariate time series; multi-equation models; predictor variables; ARIMA; stationary tests. marketing phenomena; marketing dynamics;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:now:fntmkt:1700000054. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lucy Wiseman (email available below). General contact details of provider: http://www.nowpublishers.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.