Monitoring the Dynamics of Brand Equity Using Store-Level Data

Abstract

Management of brand equity has come to be viewed as critical to the optimal long-term performance of a brand. In this paper, we evaluate the usefulness of brand equity estimates obtained from store-level data for monitoring the health of a brand. For this purpose, we use a random coefficients logit demand model calibrated on store-level scanner data to track brand equity estimates over time in two consumer packaged goods categories that experienced several new product introductions during the time period of our empirical investigation. Using these tracked measures, we also study the impact of marketing actions such as advertising, sales promotions, and product innovations on brand equity. We find that the brand equity estimates effectively capture the high equity of strongly positioned popular brands as well as brands that command a significant price premium in niche markets. Using an example, we illustrate how these brand equity estimates can be used to monitor changes in brand equity, which measures such as market share may fail to capture. Our substantive results indicate that advertising has a positive effect on brand equity in both the product categories whereas the effect of sales promotions is not significant in either category. Further, our results reveal that new product innovations have a positive impact on brand equity and can explain a significant proportion of its variation. Overall, our analysis shows a brand manager can track brand equity using store-level data, gain insights into the drivers of the brand's equity, and manage these drivers to achieve brand equity targets.

Keywords: Brand Preference, Choice Models, Advertising, Sales Promotion, Innovation, Econometric Models

JEL Classification: M37, M31, C33, D12