Understand - ing Penalty Analysis

Penalty (mean-drop) analysis is used by market researchers and product developers to gain an understanding of the product attributes that most affect liking, purchase interest or any other product-related measure. Product attributes used in penalty analysis are measured with “Just -about-right” (JAR) scales. These are categorical scales in which some points represent “too little” of a particular attribute, some points represent “too much,” and one point represents “Just -about-right” Penalty analysis measures the change in product liking (or any other measure) due to that product having “too much” or “too little” of the attribute of interest. Penalty analysis is but one of several methods used throughout the marketing research industry to reach conclusions related to the effects of a JAR variable on a different product measure. Most of these methods require substantial mathematical and statistical knowledge to implement correctly and draw appropriate inferences. At InsightsNow, we have been using, studying and writing about penalty analysis and related methods for several years; we have even developed and implemented some of our own methods. When it is implemented correctly, basic penalty analysis is a functional method that all researchers can use. This paper presents two case studies exemplifying these methods and presents recommendations for best practices.