Customer Group Cluster Analysis Based on K-Means

这篇论文研究了如何利用K-means聚类算法对客户进行细分，以帮助营销团队进行精准营销。作者使用了百度飞桨的客户群聚类数据集，其中包含性别、婚姻状况、年龄、教育、收入职业等客户信息。预处理数据后，通过轮廓系数和SSE确定最佳K值，最终将客户划分为高质量、中等质量和低质量三类。该研究提供了具体的客户细分结果，对企业营销策略制定具有一定参考价值。This paper examines how the K-means clustering algorithm can be used to segment customers to help marketing teams with precision marketing. The authors used a customer cluster dataset from Baidu Feizuo, which includes customer information such as gender, marital status, age, education, income and occupation. After preprocessing the data, the optimal K value is determined by contour coefficient and SSE, and the customer is finally divided into high quality, medium quality and low quality. The research provides specific customer segmentation results, which has certain reference value for enterprises to formulate marketing strategies.