Data-Driven User Experience Optimization: Practices and Insights from the E-Commerce Industry
Keywords:
data-driven, user experience optimization, e-commerce platform, user behavior analysis, page optimization, personalized services, conversion rate improvement, loading time optimization, A/B testing, data analysis framework, insights for the e-commerce industry, user satisfaction, interaction designAbstract
In the fiercely competitive e-commerce market, user experience is a key factor that determines the success or failure of a platform. This paper takes the e-commerce platform of Shemanquban Supply Chain Co., Ltd. as the research object and explores how to optimize user experience through data analysis. The study focuses on the in-depth mining of user behavior data and proposes a multi-dimensional data-based user behavior analysis framework that can accurately identify the points for improving user experience. By optimizing page layout, interaction design, and employing technical means to shorten page loading time, the platform has significantly enhanced user satisfaction and page retention rate. Meanwhile, the implementation of a personalized recommendation system has increased user purchase conversion rate by 22%, significantly enhancing user stickiness. The results show that data-driven optimization strategies can significantly improve user experience and platform competitiveness, providing practical experience and theoretical support for user experience optimization in the e-commerce industry.
