The product design and development insights drive the strategies of new product including price, demand, capacity, cost and return strategies. To retrieve insights of human-product interaction, user experience (UX) can be captured as the input of product design and development to enhance product quality and user satisfaction. However, it is critical to capture UX to determine appropriate user preferences and needs. This study aims to develop a text mining approach to capture UX to help product designer and developer to determine user purchase behavior and critical product features. The proposed text mining approach identifies key entities and expressions from full textual transcript of user perception. Based on term frequency and emotional scale, this study represents the ordinary scale of categorical data. The emotional adjectives (EA) and functional term (FT) of the data were analyzed to capture UX and identify user segmentation. By extracting and associating the key entities and expressions from user perception, this study identifies the features of wearable devices which trigger user purchasing behavior. The results assists designers to launch appropriate product and developer identifies the key users which will enhance user satisfaction and company competitiveness.
Relation:
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE
