Metrics That Matter

Abstract

ABSTRACT How can the importance of consumer wants and needs be quantified? Using data sets from multiple consumer brand and advertising tracking studies, several standard traditional market research techniques are compared to vector autoregression (VAR) modeling. It is demonstrated that by utilizing VAR models and resolving causal ambiguity, key performance indicators can be identified that not only correlate with traditional market research summary metrics, such as overall ratings and purchase interest, but that also drive brand sales/share and thereby qualify as metrics that matter. The analytic philosophy underlying the VAR analytic approach also is shown to be consistent with (and complementary to) market mix modeling analysis. Presented is a procedure for the simultaneous assessment of the relative and absolute impact of multiple marketing initiatives on baseline and incremental sales—including advertising and promotion effects and traditional consumer awareness and attitudinal metrics—facilitating resource-allocation decisions and providing marketers within a single framework for return on marketing investment optimization.

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