Mindset Metrics in Market Response Models: An Integrative Approach

Abstract

Demonstrations of marketing effectiveness currently proceed on two parallel tracks: quantitative researchers model the direct sales effects of the marketing mix, while advertising and branding experts trace customer mindset metrics like awareness and affect. We merge the two tracks and analyze the added explanatory value of including customer mindset 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 over 60 brands of four consumer goods shows that advertising awareness, brand consideration and brand liking account for almost one-third of explained sales variance. Interestingly, competitive and own mindset metrics make a similar contribution. Wear-in times reveal that mindset metrics can be used as advance warning signals that allow enough time for managerial action before market performance itself is affected. Specific marketing actions impact specific mindset metrics, with the strongest overall impact for distribution. Our findings suggest that modelers should include mindset metrics in sales response models, while branding experts should include competition in their tracking research.

Keywords: customer mind-set metrics, market response models, timeseries models, vector autoregressive models, forecast error