Internal preference mapping is a technique usually applied in consumer studies, in which a vector space is built based on acceptance data generated from affective tests (MacFIE; THOMPSON, 1988; LAWLESS; HEYMANN, 2010). Multivariate statistical techniques such as Multidimensional Scaling are employed to obtain a preference space, resulting in a set of acceptance vectors, in which each vector indicates a behavior of preference for each consumer