徐州市组合仪表客户分级评价数据

通过收集和分析徐州市客户对组合仪表消费相关数据，使用RFM客户价值模型，了解客户对组合仪表的购买力水平和消费偏好对客户进行等级评级，实现精准化运营，通过对客户价值管理，满足不同价值客户的个性化需求。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。另外可以为本地区客户群体高度重叠企业提供不同等级客户个性化服务的数据支持。1.数据采集：采集徐州市客户对组合仪表的相关交易数据。其中，采集数据中“下单时间”为距离统计时间最近的一次订单时间，“订单金额”指的是距离统计时间最近的这次订单金额，“历史购买总次数”“历史购买总金额”指的是历史服务时间段内统计得出的购买次数和购买金额。2.数据处理：对采集到本次订单金额（万元）、历史订单总金额（万元）等数据进行分类、合并、累加，便于分析使用，其中客户编号已进行脱敏转换处理。3.算法加工：R评分：根据用户下单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评分：消费频率评分根据历史购买总次数（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：根据历史购买总金额（Z）,划分为5个等级，0<Z≤10为1分，10＜Z≤20为2分，20＜Z≤30为3分，30＜Z≤50为4分，50<Z为5分；RFM综合评分（X）=0.3*R+0.4*F+0.6*M；客户等级分为ABC三级，0≤X≤3为C级，3＜X≤6为B级，6＜X 为A级

By collecting and analyzing customer data related to combination instrument consumption in Xuzhou City, this dataset adopts the RFM customer value model to assess customers' purchasing power levels and consumption preferences for combination instruments, conduct hierarchical rating of customers, realize precise operations, and meet the personalized demands of customers at different value levels through customer value management. For Class A customers, communicate with them 1 to 2 times per month; for Class B customers, communicate 1 to 2 times per quarter; for Class C customers, communicate 1 to 2 times every six months. In addition, it can provide data support for enterprises with highly overlapping local customer groups to deliver personalized services for customers of different tiers.

1. Data Collection: Collect relevant transaction data of customers in Xuzhou regarding combination instruments. Among the collected data, "order time" refers to the timestamp of the latest order as of the statistical time, "order amount" refers to the amount of this most recent order as of the statistical time, while "total historical purchase times" and "total historical purchase amount" refer to the purchase times and purchase amount counted within the historical service period.

2. Data Processing: Classify, merge and accumulate the collected data such as the current order amount (in ten thousand yuan) and total historical order amount (in ten thousand yuan) to facilitate analysis, and the customer IDs have been desensitized and converted.

3. Algorithm Processing:
R score: Divide into 5 levels based on the number of days (D) between the user's order 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, 1 point for D>50;
F score: Divide the consumption frequency score into 5 levels according to the total historical purchase 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, 5 points for S>15;
M score: Divide into 5 levels based on the total historical purchase amount (Z): 1 point for 0<Z≤10, 2 points for 10<Z≤20, 3 points for 20<Z≤30, 4 points for 30<Z≤50, 5 points for Z>50;
RFM comprehensive score (X) = 0.3*R + 0.4*F + 0.6*M;
Customer levels are divided into three tiers: Class C for 0≤X≤3, Class B for 3<X≤6, Class A for X>6.

搜集汇总

背景与挑战

背景概述

该数据集包含516条记录，聚焦于徐州市组合仪表客户的交易数据，采用RFM模型对客户进行分级评价，包括R、F、M评分和综合总分，以支持精准运营和个性化服务。数据来源于企业自行产生，更新频次为按需更新，适用于制造业客户价值管理场景。