大数据环境下金融业用户行为分析模型研究

Junfeng Mei, Ying Chen, Taoli Ye, Chenglong Huang, H. Ye
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引用次数: 0

摘要

随着互联网时代多元化商业模式和细分市场的快速发展,面临着高客户成本和高流动率的双重挑战,第三方服务获取统计数据不安全,埋点成本较高的问题,急需对客道进行精准定位,精细化运营,而通过对这些数据的统计研究、分析,我们可能会发现用户使用产品的规律;并与网站营销策略、产品功能、运营策略、用户体验的优化相结合,实现更精准的运营和营销,使产品更好的成长。本文基于埋点和基于客户端SDK技术的移动网络环境检测工具,通过对用户行为模块的分析,提供可视化的统计效果,操作简单,数据准确。基于Eclipse、Hadoop、Spark等技术,建立用户行为分析平台,满足用户对数据安全性和准确性的需求。
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Research on User Behavior Analysis Model of Financial Industry in Big Data Environment
Along with the age of the Internet the rapid development of diversified business model and market segments, facing high customer cost and the double challenges of high turnover rate, a third-party service access to statistical data insecurity, buried point higher cost problems, be badly in need of precise positioning for guest channels, fine operation, and through the study of the statistics, analysis of these data, we may discover the laws of users to use the product, and the law and website marketing strategy, product features, operation strategy, the combination of optimization of user experience, to achieve more accurate operation and marketing, make products better growth. Based on the buried point and the mobile network environment detection tool based on the client SDK technology, this paper will provide the visual statistical effect through the analysis of the user behavior module, with simple operation and accurate data. Based on Eclipse, Hadoop, Spark and other technologies, the user behavior analysis platform is established to meet users' needs for data security and accuracy.
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