Product style preferences: An image-based user study software concept

In the market, once producers of a particular product category become mature in their production technology, their products will have few functional differences. Thus, the greatest challenge for designers today lies in developing an appropriate design language that fits the tastes of target users. Designers use many user-study methods (interviews, questionnaires, focus groups) to understand their target users’ tastes. However, these methods mainly rely on language as the core medium of interaction. Because language can be subjective and one-sided, it is difficult to describe abstract concepts such as style preferences. In addition, in such design research, language-based information is transferred from target users to design researchers to designers over several rounds, and the objectivity and accuracy of such information can decrease substantially because of differences in people’s interpretations. This paper reviews product styling-related user study methods and technologies and proposes an image-based user study software concept that minimizes the above problems. This proposed software uses images as its main medium of interaction between target users and designers. It applies artificial intelligence technology to analyze target users’ common style preference patterns based on their image choices and sorting results. The software’s output is each target user’s persona in the form of a perceptual map and mood board. These personas provide objective product style preferences directly from the target users. This software can thus provide designers with intuitive and accurate references and inspire them to design products that meet users’ tastes and improve user experience.