Research on New Energy User Characteristics Based on Machine Learning Algorithm

Abstract

With the promotion of the “new four automobile modernizations” and the rise of users' awareness of travel service demand, user experience has penetrated into the whole process from R & D (research and development) to sales of automotive products. Based on the questionnaire survey data, this paper uses K-means algorithm to subdivide new energy users. Firstly, factor analysis and principal component analysis are used to analyze users' values and career level, then K-means clustering is carried out on this basis, and user characteristics are visually analyzed. Finally, new energy users are divided into six categories, and the car purchase preferences of each category of users are deeply analyzed, which has important theoretical and practical significance for enterprises to accurately grasp users' needs and clarify the future research and development direction.