Hedonic product optimisation: CATA questions as alternatives to JAR scales

•The use of CATA questions for hedonic product optimization was explored.•CATA questions and just-about-right (JAR) scales were compared in six consumer studies.•The same main directions for product improvement were identified by CATA questions and JAR scales.•CATA questions identified fewer deviations from the ideal than JAR scales.•Advantages and disadvantages of the two approaches are discussed.

Methodologies that identify ways products differ from consumers’ ideal are commonly used to guide innovation. In this research the use of CATA questions for this purpose was compared to JAR scales, which are well established for use in product optimization efforts. Two CATA variants were considered: (i) CATA questions including terms with hedonic-intensity connotations (e.g., not enough sweet, much too sweet), and (ii) CATA questions pertaining to both the tasted and the ideal products. In six consumer studies (n = 939), spanning multiple product categories and consumer populations (Uruguay, New Zealand and USA), it was found that CATA questions and JAR scales provided similar insights regarding the most relevant deviations from ideal. However, several differences were also identified. In particular, CATA questions tended to identify fewer deviations than did JAR scales, especially when terms with hedonic-intensity connotations were used and when differences between samples were small. This difference is likely linked to facets of the two methodologies: only applicable terms are selected when using CATA questions, whereas responses must be provided for each JAR scale included in a study. Besides, the fact that only the extreme anchors of the JAR scale were included in the CATA question could have encouraged consumers not to indicate deviations from the ideal. Penalty analysis, performed using Partial-Least Squares (PLS) regression identified several significant deviations from the ideal. While the two methodologies established the same main differences, JAR scales identified more significant deviations from the ideal than CATA questions. Although results confirmed the potential for the use of CATA questions in product optimization research, careful consideration of purpose of the research and attention to terms included in the CATA questions is recommended.