基于数据仓库的RFM用户画像构建研究
Research on the Construction of RFM User Portrait Based on Data Warehouse
叶小芹1
作者信息
- 1. 合肥城市学院 机械与电气工程学院,安徽 合肥 230000
- 折叠
摘要
随着大数据时代的到来,企业要想持久快速发展,须以客户为中心,了解不同客户群体的需求,通过海量数据的挖掘,对不断变化的客户期望迅速做出反应,并给他们提供个性化的服务.为满足企业获得更大的客户群体,论文基于电信运营商的数据,结合RFM模型提出了用户画像的构建方法,以超细分的客户标签为基础划分出不同的客户类型,实现了客户群的自助式多维分析和需求探索,为企业精准营销提供指导方法.
Abstract
With the advent of the big data era,enterprises would have to develop rapidly and per-sistently depending on their customers.It is necessary to understand the needs of different customer groups through massive data mining,respond quickly to changing customer expectations,and provide personalized services to them.In order to meet the needs of enterprises to obtain higher customer val-ue,based on the data of telecom operators and combined with RFM model,the paper proposes a meth-od for constructing user portrait,classifying different customer types based on hyper-segmented customer tags,realizing self-service multi-dimensional analysis and demand exploration of customer groups,and providing guidance methods for enterprise precision marketing.
关键词
挖掘/RFM模型/数据仓库/用户画像Key words
dig/RFM model/data warehouse/user portrait引用本文复制引用
基金项目
安徽省高校自然科学研究项目(CSZR202202)
安徽省质量工程高水平一流课程(2020kfkc172)
合肥城市学院校级重点质量工程项目(hc2021kcszsfkc001)
出版年
2024
NETL
NSTL
万方数据