Brand Hazard: A Prognostic Complement to Customer-Based Brand Equity

Existing customer-based brand equity metrics are built on customers’ choices and preferences and not on the dynamics inherent in their brand switching and timing, which potentially handicaps the prognostic ability of such metrics.   To remedy this we develop a complementary metric that focuses on the rate of change in customers’ purchase transitions. We use the counting process to model the repeat and switching rates of a brand, parse out baselines for each transition rate, cumulate these baselines over a given duration, and combine them to obtain brand hazard (BH). Using customer panel data, we estimate BH for six leading brands in three product categories over sixteen two-year moving windows.  We find increases in BH foretells future declines in the intercept of logit models of customers’ brand choice (BCI) – a customer based brand equity metric estimated from the same data. More important, we find that changes in BH and BCI are able to predict future changes in a brand’s price premium and revenue premium in the broader market.  Our findings imply that BH complements BCI, and tracking them together provides a comprehensive prognosis of a brand’s health.

Key Words:  Branding, Brand Equity, Brand Management, Hazard Models, Markov Process, Counting process