Monitoring the dynamics of brand equity using store-level data

Management of brand equity has come to be viewed as critical to a brand's optimal long-term performance. The authors evaluate the usefulness of brand equity estimates obtained from store-level data for monitoring the health of a brand. They 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 period of the empirical investigation. Using these tracked measures, the authors also study the impact of marketing actions, such as advertising, sales promotions, and product innovations, on brand equity. They find that the brand equity estimates effectively capture the high equity of strongly positioned popular brands and brands that command a significant price premium in niche markets. Using an example, the authors 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. The 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. Furthermore, the results reveal that new product innovations have a positive impact on brand equity and can explain a significant proportion of its variation. Overall, the analysis shows that 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.