基于客户画像的灵活就业人员公积金服务优化路径研究——以Q市为例

Research on the Optimization Path of Housing Provident Fund Services for Flexible Employment Based on Customer Profiling—A Case Study of Q City

摘要: 随着我国灵活就业规模持续扩大，住房公积金制度面临服务精准化挑战。本文基于Q市灵活就业人员住房公积金数据，运用客户画像技术，从基础属性、行为特征、产品偏好及风险表现等维度系统分析该群体的缴存特点。研究发现，灵活就业人员呈现显著分层特征：青年高学历群体偏好按月缴存型产品，中老年及低收入群体倾向自由缴存型，一次性趸缴型产品金额集中但接受度有限。信息获取渠道方面，微信和支付宝分别覆盖大龄低学历与年轻高学历群体，银行渠道亦呈现差异化吸引力。基于画像分析，研究提出精准推广、产品优化、政策适配与风险管控四方面服务优化路径，旨在提升灵活就业人员缴存意愿与制度包容性，为推动住房公积金制度数字化转型与普惠发展提供实证参考。

Abstract: With the continuous expansion of flexible employment in China, the Housing Provident Fund (HPF) system faces increasing challenges in providing precise and targeted services. This study utilizes HPF data for flexible employment personnel in Q City and applies customer profiling techniques to systematically analyze their contribution patterns across dimensions including basic demographics, behavioral characteristics, product preferences, and risk profiles. The findings reveal pronounced stratification within this group: young, highly educated individuals tend to prefer monthly contribution products, while middle-aged and low-income groups favor flexible contribution schemes; one-time lump-sum products concentrate funds but have limited acceptance. Regarding information channels, WeChat and Alipay primarily reach older, less-educated and younger, highly-educated segments respectively, while banking channels exhibit differentiated appeal. Based on the profiling analysis, the study proposes four service optimization pathways: targeted promotion, product refinement, policy adaptation, and risk management. These recommendations aim to enhance contribution willingness and system inclusiveness among flexible employment personnel, providing empirical guidance for the digital transformation and inclusive development of the HPF system.