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

•Use of Check-All-That-Apply (CATA) as a new way to record consumer reasons for liking and disliking products is compared to Open Comments (OC).•Similar mean liking scores and taste cluster structure with both methodologies.•Significantly higher number of likes and dislikes mentions with CATA than with OC.•Drivers of liking largely consistent under both conditions though respondents tend to focus more on taste with OC.•Lower levels of fatigue and boredom induced by the CATA task although considered as slightly more difficult to complete. 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.