Big Data Model Analysis of E-commerce Customer Relationship Management and Loyalty Programs Based on Artificial Intelligence

This study focuses on the application of customer relationship management (CRM) and membership loyalty mechanism in the e-commerce industry, combining artificial intelligence and big data technologies, constructing and analyzing several models, and systematically exploring their roles in improving customer satisfaction and enterprise operational efficiency. Various machine learning algorithms, such as K-means clustering, logistic regression, support vector machine (SVM), and linear regression, are used in the study to construct a customer value evaluation model, a customer churn prediction model, and a membership mechanism effect evaluation model, respectively. Through the empirical analysis of customer data from different industries and companies of different sizes, the results show that these AI-based models are not only able to effectively identify high-value customers and potentially churning users, but also measure the real impact of membership programs on customer loyalty. The experimental results show that AI-driven customer management systems are significantly better than traditional methods and have significant advantages in improving customer loyalty, achieving precision marketing, and optimizing service experience. It also shows that AI technology plays an increasingly important role in modern CRM systems and membership management, especially in data mining, feature selection, and model optimization, which has great potential and practical significance in promoting the digital transformation of enterprises.