Mindset Metrics in Market Response Models: An Integrative Approach

S. Srinivasan, M. VANHUELE, K. Pauwels

Journal of Marketing Research

August 2010, vol. 47, n°4, pp.672-684

Departments: Marketing, GREGHEC (CNRS)

Keywords: Customer mind-set metrics, Market response models, Time-series models, Vector autoregressive models, Forecast error variance decomposition, Leading indicators

Demonstrations of marketing effectiveness currently proceed along two parallel tracks: Quantitative researchers model the direct sales effects of the marketing mix, and advertising and branding experts trace customer mind-set metrics (e.g., awareness, affect). The authors merge the two tracks and analyze the added explanatory value of including customer mind-set metrics in a sales response model that already accounts for short- and long-term effects of advertising, price, distribution, and promotion. Vector autoregressive modeling of the metrics for more than 60 brands of four consumer goods shows that advertising awareness, brand consideration, and brand liking account for almost one-third of explained sales variance. Competitive and own mind-set metrics make a similar contribution. Wear-in times reveal that mind-set metrics can be used as advance warning signals that allow enough time for managerial action before market performance itself is affected. Specific marketing actions affect specific mind-set metrics, with the strongest overall impact for distribution. The findings suggest that modelers should include mind-set metrics in sales response models and branding experts should include competition in their tracking research.customer mind-set metricsforecast error variance decompositionleading indicatorsmarket response modelstime-series modelsvector autoregressive models