鹤壁市财务代理客户综合分析数据

通过收集和分析客户财务代理相关数据，了解客户对财务代理的购买力水平和消费偏好，从而了解该产品是否畅销，从而为本行业的所有企业制定生产策略，更好地为用户提供个性化的财务服务，对于A等级客户可每月1至2次与之沟通，对于B等级客户可每季度1至2次与之客户沟通，对于C等级客户可每半年1至2次与之沟通，从而制定更精准的财务服务营销策略。1.数据采集：采集各年各个客户对财务代理的相关交易数据。 2.数据处理：对采集到2024年1月至2024年11月的客户数据进行分类、合并、累加，便于分析使用。 3.算法加工：R评分 根据用户付费时间距离统计时间的天数（D）划分为5个等级: 0≤D≤10为5分，10＜D≤20 为4分，20＜D≤30 为3分，30＜D≤50为2分，50<D 为1分； F消费频率评分根据总服务次数（S）,划分为5个等级: 0<S≤2为1分，2＜S≤5 为2分，5＜S≤10 为3分，10＜S≤15为4分，15< S为5分； M评分根据服务总金额 （Z）,划分为5个等级，0<Z≤500为1分，500＜Z≤1000 为2分，1000＜Z≤2000 为3分，2000＜Z≤3000为4分，3000< Z为5分； RFM综合评分（X）=0.3*R+0.4*F+0.6*M；会员等级分为ABC三级，0≤X≤3为C级，3＜X≤6为B级，6＜X 为A级

This dataset is constructed by collecting and analyzing customer data related to financial agency services, aiming to understand customers' purchasing power and consumption preferences towards financial agency products, verify the market popularity of such products, formulate production strategies for enterprises in the industry, and deliver more personalized financial services to users. Targeted communication strategies are formulated for different customer tiers: communicate with Class A customers 1 to 2 times per month, with Class B customers 1 to 2 times per quarter, and with Class C customers 1 to 2 times every six months, so as to develop more precise financial service marketing strategies.
The dataset construction process includes three main stages:
1. Data Collection: Collect transaction data related to financial agency services for each customer across all years.
2. Data Processing: Classify, merge and accumulate the customer data collected from January 2024 to November 2024 to facilitate subsequent analysis work.
3. Algorithm Processing:
- R Score (Recency Score): Divided into 5 levels based on the number of days (D) between the customer's last paid time and the statistical time: 5 points for 0≤D≤10, 4 points for 10<D≤20, 3 points for 20<D≤30, 2 points for 30<D≤50, and 1 point for D>50.
- F Score (Frequency Score): Divided into 5 levels based on the total number of service times (S): 1 point for 0<S≤2, 2 points for 2<S≤5, 3 points for 5<S≤10, 4 points for 10<S≤15, and 5 points for S>15.
- M Score (Monetary Score): Divided into 5 levels based on the total service amount (Z): 1 point for 0<Z≤500, 2 points for 500<Z≤1000, 3 points for 1000<Z≤2000, 4 points for 2000<Z≤3000, and 5 points for Z>3000.
- RFM Comprehensive Score (X): Calculated as X = 0.3*R + 0.4*F + 0.6*M.
- Customer Membership Tier Division: Three membership tiers are defined based on the RFM comprehensive score: Class C for 0≤X≤3, Class B for 3<X≤6, and Class A for X>6.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于鹤壁市财务代理客户的综合分析，包含客户编号、交易时间、支付金额及基于RFM模型的评分与等级等14个字段，记录了701条以上的企业数据。其核心特点在于应用RFM算法对客户进行价值分层（A、B、C级），支持每月更新的动态分析，旨在通过评估客户购买力和消费偏好，为财务服务行业制定个性化的营销策略提供数据支撑。