Forecasting new product trial with analogous series

• Published in: Journal of business research Vol. 68; no. 8; pp. 1732 - 1738
• Main Authors: Wright, Malcolm J., Stern, Philip
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.08.2015; Elsevier Sequoia S.A
• Subjects: Analogous series; Brands; Consumer behavior; Consumer trial; Consumers; Economic forecasts; Empirical generalization; Error; First year; Forecasting; Forecasting techniques; Generalization; Marketing; Marketing management; New products; Packaged goods; Penetration growth; Pharmaceuticals; Product introduction; Studies; Analogous series; Empirical generalization; Penetration growth; New products; Consumer trial; Pharmaceuticals; Packaged goods
• ISSN: 0148-2963; 1873-7978
• DOI: 10.1016/j.jbusres.2015.03.032

This study develops a simple method for forecasting consumer trial for national product launches. The number of consumers who try a brand in its first year on the market is accurately predicted from the number trying the brand in the first thirteen weeks following launch. No information about the specific category or marketing activities is required — just a simple multiplier computed from analogous series in other markets. These analogues provide an empirical generalization that can be easily applied by practicing managers to track and forecast the success of new brand launches. When subject to an out-of-sample test involving 34 fresh data sets, the analogues demonstrated 43% reduction in mean absolute percentage error compared to the most accurate marketing science model.