A new approach to product set selection and segmentation in preference mapping

Abstract

A common problem in food product development is to identify the consumers' drivers of liking and to understand in what way they relate to the acceptance data. Usually, one will also be interested in identifying segments of consumers. The main objective of this study was to investigate the use of fuzzy clustering within the area of preference mapping when different consumer groups test different sets of products. A case study on low-fat cheese was used to explore and illustrate the proposed approach. Two groups of 57 and 58 consumers, respectively, participated in the consumer test. Based on sensory profiling, different cheese products evenly distributed in the sensory space were selected for each group. Each consumer rated their acceptance based on a blind tasting of six cheeses. One of the segments was identified to have a linear preference pattern, while the other two had non-linear patterns. © 2009 Elsevier Ltd. All rights reserved.