The ideal profiles can be used to help improving the existing products. However, this information should be carefully managed since (1) it is obtained from consumers, and (2) it describes a virtual product. In order to use the full potential of the ideal profiles, and to avoid a possible misinterpretation of the data, one has to ensure that the information collected is consistent.
The process checking for the consistency of the ideal profiles proposed here is based on the liking ratings: an ideal product should achieve higher hedonic ratings than the tested products, if it would be tested. But since the liking scores of the ideal products are unknown, they are estimated first. However, the comparison between liking scores (estimated for the ideals, measured for the tested products) would only make sense if the ideal descriptions have not been randomly given. For that matter, a hypothesis test checking for the significance of the ideal profiles is defined.
In the perfume example provided, it appears that most of the consumers did not describe their ideals randomly. In addition, the estimations of the ideals liking scores are high compared to those given to the tested products. Hence, for most of the consumers, the ideal profiles are considered as consistent according to the potential liking of their ideal profiles.