E-Commerce Customer Segmentation and Precision Marketing Strategy Based on Cluster Analysis

With the rapid development of e-commerce, customer segmentation and precision marketing have become important strategies for enterprises to enhance their competitiveness. Traditional marketing methods often rely on simple demographic characteristics, making it difficult to meet the increasingly diverse needs of customers. This article used the k-means clustering analysis method to segment e-commerce customers, aiming to provide data support for enterprises to develop personalized marketing strategies. This article collected multidimensional data from customers, iteratively assigns customers to the nearest center by selecting multiple initial center points, and updated the center points until convergence. Research showed that personalized marketing significantly improved customer conversion rates, with potential customers achieving a conversion rate of 41% in the sixth month, which was 36 % higher than the first month's 5 %. Cluster analysis provides effective methodological support for e-commerce customer segmentation and precision marketing, promoting the adaptability and competitive advantage of enterprises in dynamic market environments.