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Identifying Metrics That Matter: What Are the Real Key Performance Indicators (KPIs) That Drive Consumer Behavior?

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  • Lautman Martin R.

    (Lecturer, Marketing Departments at The Wharton School of the University of Pennsylvania, and The Smeal School of Business at Penn State University, USA)

  • Pauwels Koen

    (Professor of Marketing at Ozyegin University, Istanbul, Turkey)

Abstract

Vector auto regression (VAR) is a form of econometric modeling that is receiving increased attention in marketing research applications. It is used to observe whether potentially relevant indicators have a real impact on sales or success factors. Compared with correlation, regression and conjoint techniques, VAR models are superior because they are able to show the impact of changes over time on the basis of real business data. The research shows how VAR models are applied in different marketing settings. VAR models can filter relevant metrics from a whole set of potentially relevant performance indicators and quantify the sales impact of each variable. They further observe lead and lag effects that cannot be tracked when measurement is conducted at a single point in time. Modeling can be performed on competitive brands as well. VAR models also make it possible to test whether the same success factors that drive a category also drive the sales of each of the brands in that category.

Suggested Citation

  • Lautman Martin R. & Pauwels Koen, 2013. "Identifying Metrics That Matter: What Are the Real Key Performance Indicators (KPIs) That Drive Consumer Behavior?," GfK Marketing Intelligence Review, Sciendo, vol. 5(2), pages 46-52, November.
    • Handle: RePEc:vrs:gfkmir:v:5:y:2013:i:2:p:46-52:n:8
    DOI: 10.2478/gfkmir-2014-0017
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