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Modeling Dynamic Relations Among Marketing and Performance Metrics

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  • 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
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    References listed on IDEAS

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    7. Marc Vanhuele & Shuba Srinivasan & Koen Pauwels, 2010. "Mindset Metrics in Market Response Models: An Integrative Approach," Post-Print hal-00528411, HAL.
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    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.

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    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

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