Internal preference mapping and the issue of satiety

Internal preference mapping (IPM) and Landscape Segmentation Analysis® (LSA) are two techniques broadly used to unfold consumers' overall product liking ratings and create spatial maps that will provide further insights on consumers' preferences. IPM is based on a vector model while LSA involves an ideal point model. Through a simulation and the analysis of 27 market research data sets, it is shown that IPM consistently creates a hedonic dimension that prevents the identification of satiety prone attributes (intensities higher or lower than a optimal level being disliked by the consumers) on that dimension. As a result, subsequent steps taken upon generating an IPM map such as the investigation of drivers of liking, population segmentation and the estimation of optimal product profiles have also a strong likelihood of resulting in distorted results, the level of distortion being dependent on the actual configuration of the underlying structure that IPM tried to uncover. It is also shown that a technique based on ideal points such as LSA does not exhibit this systematic artifact when unfolding liking data. Consequently, sensory scientists and market researchers should use caution when interpreting and using results issued from an internal preference mapping analysis.

► Internal preference mapping creates maps with a strong hedonic dimension. ► That dimension cannot handle satiety, i.e., attributes with an optimal intensity level (not too strong, not too weak). ► Post hoc analyses such as the identification of true drivers of liking will be strongly biased. ► Ideal point models such as that used in Landscape Segmentation Analysis® do not exhibit the same limitations.