Cluster analysis is often used to group consumers based on their hedonic responses to products. We give a motivating example in which conventional cluster analyses converge on a solution where consumers do not agree on which products they like. We show why this occurs. We state a goal: to group together consumers who have a shared opinion of which products
Consumers are diverse in their product perceptions. But within the consumer population there are often consumer segments whose product perceptions are relatively homogeneous. To discover these consumer segments, consumers’ product-related responses are submitted to a cluster analysis. The particular cluster analysis is chosen by the researcher. But the choice of clustering algorithm can have profound consequences on the clustering solution
Brettanomyces spoilage in wine is due to the production of metabolites, which together create the distinctive ‘Bretty’ aroma and flavor profile associated with wine. The objective of this study was to assess the influence of three wine flavor matrices on consumer acceptance and the temporal sensory properties of wines containing high and low concentrations of Brettanomyces-metabolites. A commercial Shiraz red
Brettanomyces spoilage in wine is due to the production of metabolites, which together create a distinctive ‘Bretty’ aroma and flavor profile. The objective of this study was to assess the influence three wine flavor matrices have on consumer perception and acceptance of wines containing high and low concentrations of Brettanomyces-metabolites. A commercial Shiraz wine was altered through additions of whiskey
Ralph Waldo Emerson once cautioned that “a foolish consistency is the hobgoblin of little minds.” In this talk, this quote is playfully considered in light of consumer diversity as manifested in sensory evaluation studies.
The feelings, tastes, flavors, and sounds elicited by ready-to-eat breakfast cereals in the mouth are perceived dynamically, and evolve within each bite, and over the multi-bite eating experience. Temporal check-all-that-apply (TCATA) is a temporal sensory method that extends the use of check-all-that-apply questions by allowing continuous selection of attributes based on applicability or noticeability. TCATA can permit characterization of the
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