Consumer segmentation of BIB liking data of 12 cabernet sauvignon wines: A case study
Consumer testing of beverage alcohol has a number of serious challenges. The effect of consumption of alcohol is a limiting factor in obtaining complete block data. Collecting consumer data over several days affects the quality of the consumer response. 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 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. A total of 11 sessions were conducted at 5 LCBO store locations.
Three approaches were used to provide dummy variables for the missing data in each set. The average response for the panellist was inserted into the missing data points. The product average was substituted in a second data analysis and finally the overall mean was used in the third data set. Each approach was subjected to Qannari Clustering (Senstools 3.3.1) and 3, 4 and 5 Cluster solutions were considered. Grouping of products based on descriptive sensory data provided an external validation of the selection of sensory segments. A four cluster solution using the panellist mean produced clusters that were well explained by the sensory contrasts.
Findlay, C.J. (2008). Consumer segmentation of BIB liking data of 12 cabernet sauvignon wines: A case study. In: 9th Sensometrics Meeting. July 20-23, St. Catharines, Canada