<p>Digital shopping requires a large amount of collection, transmission and analysis of customer behavior data to understand customer needs and enhance the shopping experience. However, the frequent data leakage incidents and cyber attacks in recent years have seriously threatened customers’ privacy and trust, leading to a decline in customer satisfaction. The research has constructed a data acquisition system based on intelligent tag sensors, ensuring the security and integrity of data during the acquisition and transmission process through encryption algorithms and identity verification mechanisms. Optimize the anti-interference ability of sensors by applying electromagnetic field theory to reduce the risk of data tampering. The research utilizes behavioral data analysis and modeling techniques to deeply explore customer purchasing behavior, loyalty and churn patterns, and construct an accurate customer behavior model. Through this model, enterprises can promptly perceive changes in customer demands, adjust product strategies and service plans, and thereby enhance customer satisfaction. The research results show that the combination of intelligent tag sensors and behavioral modeling technology can significantly enhance customer satisfaction while ensuring the security of network data. Experimental data shows that the intelligent tag sensor system with encrypted transmission reduces the risk of data leakage, enhances customers’ satisfaction with privacy protection, and the customer behavior model based on this system has a high prediction accuracy rate, which helps enterprises precisely formulate personalized marketing strategies. The repeat purchase rate of customers increases and the complaint rate decreases. The effectiveness of this research method in ensuring data security and enhancing customer satisfaction has been fully verified.</p>