Big data-driven precision marketing model and system optimization for bank customers
大数据驱动的银行客户精准营销模型与系统优化

摘要

大数据技术在银行客户精准营销中的应用逐渐成为提升业务效益的重要手段。基于客户行为数据和金融信息，银行能够更精确地了解客户需求，进而制定个性化营销策略。本研究提出了一种大数据驱动的银行客户精准营销模型，结合数据挖掘、机器学习算法和数据分析技术，实现了对银行客户的深度洞察与精准预测。通过优化营销策略和提升客户体验，银行可以实现更高的客户转化率和忠诚度。本论文还探讨了现有模型的应用场景及其局限性，并提出了相应的改进方案。

Abstract

The application of big data technology in precision marketing for bank customers has gradually become an important means to improve business efficiency. Based on customer behavior data and financial information, banks can more accurately understand customer needs and then formulate personalized marketing strategies. This study proposes a big data-driven precision marketing model for bank customers, which combines data mining, machine learning algorithms, and data analysis technologies to achieve in-depth insight and accurate prediction of bank customers. By optimizing marketing strategies and enhancing customer experience, banks can achieve higher customer conversion rates and loyalty. This paper also discusses the application scenarios and limitations of existing models, and puts forward corresponding improvement plans.