Segmentation of BIB consumer liking of high-fatigue products: Sensory confirmation of statistical methods
Consumer testing of products which create sensory fatigue have a number of serious challenges. The effect of consumption of alcoholic beverages, extremely spicy foods, intense flavors or numbing ingredients limit the collection of complete block data to a small number of samples. If a study with a large number of samples is conducted by collecting consumer data over several days, learning affects the quality of the consumer responses. By the third day, most consumers are behaving like trained assessors, a conclusion that is supported by the decrease in first position effect.
Typically, segmentation of consumer liking data requires a complete block. In this study, 12 commercially available Cabernet Sauvignon wines were evaluated by over 600 red wine consumers in a 12 present 3 Balanced Incomplete Block design. Each consumer tasted 3 of the wines in a single 10 minute session, with demographic questions providing a break between samples. The means for all 12 wines ranged from 5.7 to 6.3 on the 9-point hedonic scale. Without segmentation of the consumers the results were not actionable. It was essential to determine clusters based on consumer liking. But a complete block of data had to be created. To compensate for the missing data points, the average response of each panellist was inserted into the nine missing data points. The total data set was treated by Qannari Clustering (Senstools 3.3.1).
Two additional mathematical approaches were used to cluster the data and provided comparable conclusions. Descriptive sensory data of the clustered products provided an external validation of the selection of four consumer liking segments. The clusters ranged in size from 17 to 32% and each had distinct sensory differences that were understood by winemakers. The liking range within each cluster expanded to around 4 to 8 on the 9-point scale. This approach to segmentation of large BIB studies with small incomplete blocks that combine sensory driven design with a specific clustering procedure appears to be very promising.
Findlay, C.J., Meullenet, J.-F., & McNicholas, P. (2009). Segmentation of BIB consumer liking of high-fatigue products: Sensory confirmation of statistical methods. In: 8th Pangborn Sensory Science Symposium. July 26-30, Florence, Italy.