Enhancing Network Marketing Strategy Optimization and Performance Evaluation Through Data Mining

The purpose of this study is to explore the role of data mining in the optimization of network marketing strategy and evaluate its effect. In view of the growing trend of big data in the current Internet era, enterprises need to use data mining technology to tap the potential value in user behavior data, so as to optimize marketing strategies and enhance market competitiveness. In this study, data mining techniques such as association rules mining are adopted, and the application effect of data mining in network marketing strategy optimization is evaluated by combining empirical analysis and case study. It is found that data mining provides valuable market insight for enterprises, enabling enterprises to better understand users’ preferences, behavior patterns and buying habits. Through the implementation of personalized recommendation, precision marketing and other strategies, enterprises can improve user purchase conversion rate and customer satisfaction, and enhance market competitiveness. In addition, mining association rules provides important enlightenment for product recommendation and promotion, helping enterprises to better meet users’ needs and increase sales and market share. Neural network can be used to predict consumers’ purchase intention and preference, and provide strong support for personalized recommendation. Data mining has great influence and value on the optimization of network marketing strategy. By mining and analyzing massive data, enterprises can understand users more deeply and grasp market trends more accurately, so as to optimize and refine marketing strategies and enhance competitiveness and profitability.