Susanne Bølling Johansen1,2, Margrethe Hersleth1,2, Jorun Øyaas 3 and Tormod Næs1,4
1 Matforsk, Norwegian Food Research Institute, Norway
2 Department of Chemistry, Biotechnology and Food Science, The Norwegian University of Life Sciences, Norway
3 Tine BA, Norway
4 Department of Mathematics, University of Oslo, Norway
A common problem in product development of consumer products is to identify the drivers of liking in the actual market and the ideal point of the product attributes. Usually one will also be interested in identifying segments of consumers with similar preference pattern. A number of techniques are available for this purpose.
The objective of this study is to investigate the use of fuzzy clustering for segmenting consumers and thereby to investigate and perhaps find ideal points of preference.
For a detailed study of the preference surface within each segment one should preferably cover as large parts as possible of the product region of interest. However, in practise it is usually impossible for consumers to assess a large number of products. In this paper we therefore proposed to serve different consumers different samples. In order to get as much information as possible from each consumer and for the purpose of avoiding segments based on only one part of the region, it is proposed that each consumer is given samples from different parts of the interesting region.
In the present study two groups of about 60 consumers participated in the consumer test. Based on a sensory profiling, different low fat cheese samples covering the region were selected for each of the two groups. Each group first completed a blind tasting of six cheeses. In a second session the same six cheeses were tasted with information about the fat content. The consumers rated the cheeses for acceptance and buying probability. Socio- and demographic data were collected as well as attitudes towards relevant issues using different validated attitude scales.
The focus of this presentation lies on investigating the strengths and weaknesses of this method and how to explore possible interactions between consumers’ sensory perception and influence of product information.
