Use of Check-all-that-apply (CATA) and penalty analysis for product development guidance: a case study with Mexican-style sources

Abstract

In the industrial setting, one common inclusion in consumer testing is the measurement of consumer reaction to specific product attributes to provide product developers guidance for optimization. Just about right (JAR) scales are a popular choice for obtaining this re-formulation guidance when combined with overall liking to determine the potential impact of responses to overall acceptance. Since 2007, the practice of using Check-all-that-apply (CATA) in various consumer applications has steadily increased. CATA has been used successfully with consumers to understand the sensory characteristics of products. With the increasing popularity of the tool, researchers are studying new ways to analyze CATA data, including applying penalty analysis. However, scant literature exists to compare the outcomes from using JAR scales and CATA for guiding product development. In the present work, two approaches for eliciting hedonic and attribute responses from consumers were compared: one using Just About Right (JAR) scales for rating key attributes and the other Check-All-That-Apply to identify consumer likes and dislikes. Two separate sets of consumers evaluated the same 4 Mexican-style sauce products using one of the two methods in a central location test. Penalty analysis was used to help analyze the data and the interpretation of each data set and the subsequent guidance recommendations for product development were compared. There is a striking agreement between the penalties obtained from each method. Some advantages and disadvantages of both question types are discussed. Thus, intensity-rated CATA questions may have potential use as an alternative to JAR questions for providing formulation optimization guidance within the food manufacturing industry.