摘 要
随着信息技术的迅猛发展，大数据技术为各行业带来了前所未有的机遇与挑战，客户关系管理作为企业提升竞争力的关键环节，亟需借助大数据技术实现转型升级。本研究旨在构建基于大数据的客户关系管理系统，以期为企业提供更精准、高效的客户管理方案。通过分析大数据环境下客户数据的特点，采用数据挖掘、机器学习等先进技术手段，设计了涵盖数据采集、存储、处理及分析等功能模块的系统架构。该系统能够实时获取多源异构客户数据，运用关联规则挖掘算法发现潜在客户需求，利用分类预测模型评估客户价值并预测流失风险。经实际应用测试表明，系统可显著提高客户满意度和忠诚度，降低运营成本，增强企业的市场响应能力。创新性地将大数据技术与传统CRM理念深度融合，突破了原有系统的数据处理能力和决策支持水平限制，为现代企业客户关系管理提供了全新的思路与方法，具有重要的理论意义和实用价值。
关键词：大数据客户关系管理；数据挖掘与机器学习；客户价值评估；流失风险预测；多源异构数据处理
Abstract
With the rapid advancement of information technology, big data technology has brought unprecedented opportunities and challenges to various industries. As a critical component for enhancing corporate competitiveness, customer relationship management (CRM) urgently requires transformation and upgrading through the integration of big data technology. This study aims to construct a big data-based CRM system to provide enterprises with more precise and efficient customer management solutions. By analyzing the characteristics of customer data in a big data environment, advanced techniques such as data mining and machine learning are employed to design a system architecture that encompasses functions including data collection, storage, processing, and analysis. The system is capable of real-time acquisition of multi-source heterogeneous customer data, utilizing association rule mining algorithms to uncover potential customer needs, and applying classification and prediction models to evaluate customer value and predict churn risk. Practical application tests have demonstrated that the system can significantly enhance customer satisfaction and loyalty, reduce operational costs, and improve market responsiveness. Innovatively integrating big data technology with traditional CRM concepts, this approach overcomes limitations in data processing capabilities and decision-support levels of existing systems, offering modern enterprises a new perspective and methodology for customer relationship management, which holds significant theoretical implications and practical value.
Keywords：Big Data Customer Relationship Management；Data Mining And Machine Learning；Customer Value Evaluation；Churn Risk Prediction；Multi-source Heterogeneous Data Processing
目 录
摘 要 I
Abstract II
引 言 1
第一章 大数据与客户关系管理概述 2
1.1 客户关系管理概念解析 2
1.2 大数据技术基础 2
1.3 大数据对 3
第二章 系统需求分析与架构设计 5
2.1 业务需求分析 5
2.2 系统架构规划 5
2.3 数据处理流程设计 6
第三章 关键技术实现与应用 8
3.1 数据采集与预处理 8
3.2 数据存储与管理 8
3.3 数据分析与挖掘算法 9
第四章 系统实施与效果评估 11
4.1 实施方案制定 11
4.2 用户体验优化 11
4.3 效果评估与反馈 12
结 论 14
参考文献 15
致 谢 16
