摘 要
客户关系管理（CRM）作为现代企业管理的重要组成部分，其核心在于通过有效的客户细分实现精准营销和服务优化。随着市场竞争日益激烈和消费者需求日趋多样化，传统客户细分方法已难以满足企业精细化运营的需求。本研究旨在探讨当前客户关系管理中客户细分存在的问题并提出针对性对策，以提升企业客户管理水平。通过对国内外相关文献的系统梳理，结合实际案例分析，发现现有细分方法存在静态化、单一化以及缺乏动态调整机制等不足之处。为此，本文引入大数据分析技术和机器学习算法，构建了基于多维度特征融合的动态客户细分模型，该模型能够实时捕捉客户行为变化并自动调整细分标准。实证研究表明，新模型不仅提高了客户细分精度，还增强了预测准确性，为企业制定个性化营销策略提供了科学依据。此外，研究还提出了建立客户生命周期管理体系、强化数据安全保护等配套措施，确保客户细分成果得到有效应用。本研究创新性地将新兴技术与传统CRM理论相结合，在方法论层面实现了突破，为推动我国企业客户关系管理现代化进程提供了有益参考。
关键词：客户关系管理 客户细分 大数据分析
Abstract
Customer Relationship Management (CRM) as an essential component of modern enterprise management focuses on achieving precise marketing and service optimization through effective customer segmentation. As market competition intensifies and consumer demands become increasingly diverse, traditional customer segmentation methods have struggled to meet the requirements of refined corporate operations. This study aims to explore existing issues in customer segmentation within current CRM practices and propose targeted strategies to enhance corporate customer management capabilities. Through a systematic review of relevant domestic and international literature combined with case study analysis, it is found that existing segmentation methods suffer from deficiencies such as static nature, singularity, and lack of dynamic adjustment mechanisms. To address these challenges, this paper introduces big data analytics and machine learning algorithms to construct a dynamic customer segmentation model based on multi-dimensional feature fusion. This model can capture real-time changes in customer behavior and automatically adjust segmentation criteria. Empirical studies show that the new model not only improves the accuracy of customer segmentation but also enhances predictive precision, providing a scientific basis for formulating personalized marketing strategies. Furthermore, the research proposes complementary measures such as establishing a customer lifecycle management system and strengthening data security protection to ensure the effective application of segmentation outcomes. Innovatively integrating emerging technologies with traditional CRM theories, this study achieves a breakthrough at the methodological level, offering valuable references for advancing the modernization of customer relationship management in Chinese enterprises.
Keyword:Customer Relationship Management Customer Segmentation Big Data Analysis
目 录
引言 1
1客户细分的理论基础与意义 1
1.1客户细分的概念界定 1
1.2客户细分在 2
1.3理论研究对实践的指导意义 2
2客户细分的主要问题分析 3
2.1数据收集与处理难题 3
2.2细分标准的选择困境 3
2.3动态变化应对不足 4
3有效的客户细分策略构建 4
3.1基于多维度的数据整合 4
3.2智能化细分技术的应用 5
3.3构建灵活细分模型框架 6
4客户细分实施对策与保障 6
4.1细分结果的有效应用 6
4.2细分体系持续优化机制 7
4.3企业内部协同支持体系 7
结论 8
参考文献 9
致谢 10
