UCLA

Managers are unlikely to keep current with advanced developments in market-response analysis, and technical analysts often lack the market-place knowledge of the many product categories they must track through syndicated data; this is a recipe for bad decisions. The authors present methods based on three-mode factor analysis and multivariate regression that can help both analysts and managers make better decisions regarding whether UPCs should be aggregated into brand units and, if so, how should the aggregation be done; which marketing instruments to track; and how to disentangle correlated promotional strategies. The practicality of this approach is demonstrated by an application to UPC-level data (25 UPCs, seven marketing instruments, and 156 weeks). In this example, to aggregate UPCs within a manufacturer into brand units would distort the relations between the marketing instruments and market responses. A multivariate regression from the competitive-component scores provides a methodologically sound and practical method for calibrating market response in such cases.