Research on Low-Cost Precision Marketing and Application Framework from the Perspective of User Segmentation

• 1、School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing, 100876

Abstract：With the rapid development of e-commerce, precision marketing has become a critical strategy for enhancing user experience and optimizing resource utilization efficiency. This study aims to develop a low-cost precision marketing framework by analyzing user behavior characteristics and applying the K-means clustering algorithm for user segmentation, enabling the formulation of person alized marketing strategies. Based on e-commerce platform user data, the study integrates user profile, behavior, and preference features to construct a refined segmentation model and proposes a differentiated marketing strategy framework applicable to multiple industries. The results reveal significant behavioral and preference differences among user groups, demonstrating that targeted strategy optimization can effectively improve marketing conversion rates. This research not only provides theoretical support for enterprises to optimize marketing strat egies under resource constraints but also offers a practical framework and action able guidance for precision marketing across diverse industries.

Keywords： Precision marketing User segmentation K-means clustering Low Cost strategies Cross-Industry applications