Research on Purchasing Behavior Pattern of E-commerce Platform Consumers Based on Big Data Analysis

In the era of booming e-commerce, consumer purchasing behaviors are becoming more complex. This study combines consumer behavior theory with big data analysis to explore the characteristics and patterns of e-commerce platform consumers' purchasing behavior. It innovatively reveals the joint influence of personal characteristics, product attributes, and platform environments on purchasing decisions, constructs a real-time dynamic prediction model, and establishes a "predict-response" closed-loop system. The research refines the theoretical framework of e-commerce consumer behavior, provides practical strategies for platforms such as personalized recommendations and cost optimization, and is applicable to various e-commerce models. However, it also faces challenges like balancing data utility and privacy protection. Future research can focus on incorporating social media sentiment analysis, examining the impact of sustainability labels, and exploring consumer behavior in the metaverse.