Understanding consumer perceptions is crucial when dealing with complex topics such as sustainability and the value of Made in Italy. Rating data are often collected through surveys to capture these attitudes, but their analysis requires specific statistical tools. In this seminar, I will provide an overview of the CUB (Combination of a Uniform and a shifted Binomial) model, specifically proposed for the analysis of rating data. After introducing the main aspects of the CUB model and the CUB family, I will focus on recent developments in model-based clustering of ordinal data within this framework. The methodology will be illustrated through a case study conducted in the context of the MICS (Made in Italy - Circular e Sustainable) project, where consumersâ€^TM perceptions regarding sustainability and Made in Italy were investigated.