E-Commerce User Behavior Analysis and Prediction Based on Artificial Neural Network and Data Mining

This study aims to explore strategies for analyzing and predicting e-commerce user behavior through artificial neural networks and data mining technology. The research first aims to achieve a precise understanding of user needs and behaviors by building detailed and rich user profiles, including users' basic information, hobbies, and consumption habits. Based on this comprehensive user data, a series of experiments were designed and implemented using artificial neural networks and data mining technology to establish a comprehensive user behavior prediction model. The experimental results demonstrate that the model effectively analyzes and predicts users' purchasing intentions and consumption patterns. Based on the model's findings, this study also proposes a series of optimization strategies and application suggestions for e-commerce platforms, including marketing s-trategy optimization and service quality improvement, with the aim of promoting the sustainable development of e-commerce platforms and enhancing the overall user experience. The findings and suggestions of this study are expected to provide valuable references for the e-commerce industry, facilitating significant progress in user behavior analysis and business optimization.