The main objective of the project is to create a web App to interactively display the analysis of data from kansei engineering studies. Kansei engineering is a tool used in emotional product design and aims to discover which product features convey a specific set of emotions and feelings. The project will include the development of analytical tools and the creation of graphics to visualize results. The application will be programmed with the language R together with the extension Shiny, which will create an easy to use interactive platform. The application is primarily directed to the sector of product design, where statistical knowledge is often scarce, so results are displayed in a visually appealing and easy to interpret manner. The App obtained has been modularised, pursuing a structured code and the possibility to expand it easily in the future. After the upload of data from any kansei engineering study, it helps the user to analyse it. It gives all information necessary to know which product features affect which emotions and gives a measure of how much. The App has a sequential workflow, and the last step gives the user a suggestion of the features that the product should have, according to his or her requirements. This has been achieved through a multicriteria optimization model that has been specially adapted for kansei engineering studies. The App has also some further settings that can be modified, for example it offers the possibility to stratify all the results (say, by gender), if this information was given in the preliminary data set.