宁波市阿里国际站代运营服务客户分级评价数据

通过收集和分析宁波市客户对阿里国际站代运营服务消费相关数据，使用RFM客户价值模型，了解客户对阿里国际站代运营服务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：采集宁波市客户对阿里国际站代运营服务的相关交易数据。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≤0.5为1分，0.5＜Z≤1为2分，1＜Z≤2为3分，2＜Z≤5为4分，5<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

This dataset is constructed by collecting and analyzing consumption data of customers in Ningbo regarding third-party agency operation services for Alibaba International Station, and leveraging the RFM customer value model to evaluate the purchasing power and consumption preferences of these customers, conduct tiered rating of customers, implement precise operations, and meet the personalized demands of customers at different value levels. For Tier A customers, conduct communication 1 to 2 times per month; for Tier B customers, 1 to 2 times per quarter; for Tier C customers, 1 to 2 times every six months. Additionally, it can offer data support for enterprises with highly overlapping local customer groups to provide personalized services for customers of different tiers.

1. Data Collection: Collect relevant transaction data of Ningbo customers for the agency operation services on Alibaba International Station. Specifically, the "order time" in the collected data refers to the timestamp of the most recent order relative to the statistical time; the "order amount" refers to the amount of that most recent order; the "total number of historical purchases" and "total historical purchase amount" refer to the total purchase count and total purchase amount calculated over the historical service period.
2. Data Processing: Classify, merge, and accumulate the collected data including the current order amount (in ten thousand yuan) and total historical order amount (in ten thousand yuan) to facilitate subsequent analysis. All customer IDs have undergone desensitization conversion processing.
3. Algorithm Processing:
- R Score: Divided into 5 tiers based on the number of days (D) between a customer's order timestamp 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: The consumption frequency score is divided into 5 tiers based on the total number of historical purchases (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: Divided into 5 tiers based on the total historical purchase amount (Z): 1 point for 0 < Z ≤0.5, 2 points for 0.5 < Z ≤1, 3 points for 1 < Z ≤2, 4 points for 2 < Z ≤5, and 5 points for Z >5;
- RFM Comprehensive Score (X) = 0.3*R + 0.4*F + 0.6*M;
- Customer tiers are divided into three levels: Tier C for 0 ≤ X ≤3, Tier B for 3 < X ≤6, and Tier A for X >6.

搜集汇总

背景与挑战

背景概述

该数据集是宁波市亿人网络科技有限公司登记的数据知识产权，包含532条宁波市客户对阿里国际站代运营服务的消费记录，用于基于RFM客户价值模型进行客户分级评价。数据集通过分析下单时间、消费频率和消费金额等字段，计算R、F、M评分及综合得分，将客户划分为A、B、C三个等级，以支持精准化运营和个性化服务，例如针对不同等级客户制定差异化的沟通策略。