External preference segmentation with additional information on consumers: A case study on apples

We consider hedonic studies when, in addition to liking scores, external information is available on the products (i.e. sensory descriptors) as well as on the consumers (demographic, usage and attitude attributes). The classification around latent variables (CLV) methodology may be used for segmentation purposes in such situations. Two alternative strategies have been compared on the basis of a case study on 31 apple varieties according to the use a priori or a posteriori of the consumer attributes. The direct approach, L-CLV, which involves the three blocks of information (product hedonic scores, product sensory descriptors and consumer attributes) simultaneously, has demonstrated its ability to reveal a segmentation of consumers associated with a large number of sociological and behavioral parameters, in relation to the key sensory drivers. On the contrary, using a two-step procedure, with first an external preference segmentation by taking into account only the external information on products, no relevant information was gained with the subsequent use of the consumer attributes. For a better investigation of consumer preferences from a marketing research point of view, it appears that it is much more relevant to introduce both types of external information simultaneously and that L-CLV is suitable for this purpose.

[1]  N. M. Faber,et al.  Simple improvement of consumer fit in external preference mapping , 2003 .

[2]  Tormod Næs,et al.  Combining extrinsic and intrinsic information in consumer acceptance studies , 2012 .

[3]  Tormod Næs,et al.  A new approach to product set selection and segmentation in preference mapping , 2010 .

[4]  E. Vigneau,et al.  Clustering of Variables Around Latent Components , 2003 .

[5]  E. Martinsdóttir,et al.  Sensory characteristics of different cod products related to consumer preferences and attitudes , 2009 .

[6]  H. J. H. MacFie,et al.  Preference mapping in practice , 1994 .

[7]  L. Lebart,et al.  Statistique exploratoire multidimensionnelle , 1995 .

[8]  V. Cariou,et al.  Quadratic PLS regression applied to external preference mapping , 2014 .

[9]  Per B. Brockhoff,et al.  Heterogeneity in consumer preference data : A combined approach , 1997 .

[10]  Jean-Xavier Guinard,et al.  How do consumer hedonic ratings for extra virgin olive oil relate to quality ratings by experts and descriptive analysis ratings , 2011 .

[11]  Tormod Næs,et al.  Consumer preference mapping of dry fermented lamb sausages , 1997 .

[12]  M. Wedel,et al.  A Clusterwise Regression Method for Simultaneous Fuzzy Market Structuring and Benefit Segmentation , 1991 .

[13]  Ian Wakeling,et al.  Designing consumer trials balanced for first and higher orders of carry-over effect when only a subset of k samples from t may be tested , 1995 .

[14]  Suzanne Winsberg,et al.  A latent class vector model for preference ratings , 1993 .

[15]  Christopher J. Findlay,et al.  Multivariate and Probabilistic Analyses of Sensory Science Problems , 2007 .

[16]  P. Courcoux,et al.  Preference mapping using a latent class vector model , 2001 .

[17]  Harald Martens,et al.  Regression of a data matrix on descriptors of both its rows and of its columns via latent variables: L-PLSR , 2005, Comput. Stat. Data Anal..

[18]  Evelyne Vigneau,et al.  Classification de variables autour de composantes latentes , 2006 .

[19]  Tormod Næs,et al.  Statistics for Sensory and Consumer Science , 2010 .

[20]  Dave Plaehn.  A variation on external preference mapping , 2009 .

[21]  El Mostafa Qannari,et al.  Finding and explaining clusters of consumers using the CLV approach , 2011 .

[22]  Tormod Næs,et al.  New modifications and applications of fuzzy C-means methodology , 2008, Comput. Stat. Data Anal..

[23]  Tormod Næs,et al.  Identifying and interpreting market segments using conjoint analysis , 2001 .

[24]  Evelyne Vigneau,et al.  Segmentation of consumers taking account of external data. A clustering of variables approach , 2002 .

[25]  Pieternel A. Luning,et al.  Internal versus external preference analysis : an exploratory study on end-user evaluation , 2006 .