To avoid flops, the control of the risks in product innovation and the reduction of the innovation cycles require valid and fast customer's assessments. A methodology must be proposed to the designer to take into account the perceptions of the user. The method presented is based on an iterative process of user selection of representative CAD models of the product. An IGA is used to interpret the user's choices and introduce new products. In the center of this methodology, the user who, thanks to his decisions, will guide the evolution of the algorithm and its convergence. After a description of the IGA, a study on the convergence of the IGA is presented, according to the tuning parameters of the algorithm and the size of the design problem. An experiment was carried out with a set of 20 users on the application case proposed a steemed glass. The implementation of the perceptive tests and the analysis of the results, using Hierarchical Ascendant Classification (HAC) is described. The main contributions of the paper are proposals of (1) an interactive product optimization methodology; (2) a procedure for parameterizing interactive genetic algorithms; (3) a detection of perceptive trends that characterize customer expectations; (4) an experimental application on a real life product.