Comparison of open comments and check-all-that-apply to collect reasons for liking and disliking chocolates in preference mapping

Abstract

Collecting Open Comments (OC) is a common way to learn about the product features that consumers like and dislike in internal preference mapping studies. OC has the advantage to provide a direct answer to the question “What do you like/dislike about this product?” without consumers. However, because OC does not suggest any sensory terms, consumers sometimes struggle to properly verbalize their perceptions leading to data and information that are difficult to interpret and translate into product improvement recommendations. In addition, the encoding of OC is a cumbersome, time-consuming, and possibly expensive task depending on the context of study. In this context, we explored the use of the Check-All-That-Apply (CATA) method as an alternative to OC to collect reasons for like and dislike reported by consumers. We conducted two parallel studies in which respondents evaluated 6 out of 8 milk chocolates using an incomplete block design. The only noticeable difference between the two studies was that respondents reported reasons for liking and disliking using either OC (n = 204) or CATA (n = 157). Results did not show any striking difference between mean overall liking scores and taste clusters in both studies. The drivers of liking and disliking associated with each product were also largely consistent, although some differences in citation rates and attitudes were noted. For instance, respondents tended to disregard appearance and texture in favor of flavor with OC as compared to CATA. In addition, the drivers of disliking provided by OC were less diverse and less frequently cited than in CATA. Overall, our results suggest that CATA is a promising alternative to OC for liking-oriented product description provided that special care is taken to build a relevant list of CATA terms.