Consumer Attitude Metrics For Guiding Marketing Mix Decisions


Marketing Science

juillet-août 2014, vol. 33, n°4, pp.534-550

Départements : Marketing, GREGHEC (CNRS)

Mots clés : Consumer attitude metrics, Responsiveness, Potential, Stickiness, Sales conversion, Hierarchical linear model, Cross-effects model, Empirical generalizations, Dynamic programming model, Optimal marketing resource allocation

Marketing managers often use consumer attitude metrics such as awareness, consideration, and preference as performance indicators because they represent their brand's health and are readily connected to marketing activity. However, this does not mean that financially focused executives know how such metrics translate into sales performance, which would allow them to make beneficial marketing mix decisions. We propose four criteria—potential, responsiveness, stickiness, and sales conversion—that determine the connection between marketing actions, attitudinal metrics, and sales outcomes.We test our approach with a rich data set of four-weekly marketing actions, attitude metrics, and sales for several consumer brands in four categories over a seven-year period. The results quantify how marketing actions affect sales performance through their differential impact on attitudinal metrics, as captured by our proposed criteria. We find that marketing–attitude and attitude–sales relationships are predominantly stable over time but differ substantially across brands and product categories. We also establish that combining marketing and attitudinal metrics criteria improves the prediction of brand sales performance, often substantially so. Based on these insights, we provide specific recommendations on improving the marketing mix for different brands, and we validate them in a holdout sample. For managers and researchers alike, our criteria offer a verifiable explanation for differences in marketing elasticities and an actionable connection between marketing and financial performance metrics