马鞍山地区公司平台客户价值评估数据

采集销售记录表中马鞍山地区的数据，通过客户在2018年4月1日距离2025年7月1日间隔的最近一次消费时间天数R、客户在2018年4月1日至2025年7月1日之间消费频次F和客户在2018年4月1日至2025年7月1日之间消费金额M（单位：元）， 采用 RFM 模型对客户进行价值评级，实现精准化运营，通过对马鞍山地区客户价值管理，满足不同价值客户的个性化需求。对A级客户，每个月进行一次回访维护，对B级客户，每个季度进行一次回访维护，对C级客户每半年进行一次回访维护，对D级客户每年进行一次回访维护。另外可以为本地区客户群体高度重叠企业提供不同价值类型的客户个性化服务的数据支持。对从销售记录表中采集到的数据进行脱敏、降噪、清洗、聚集、分析。2、数据加工：运用RFM模型结合客户在2018年4月1日距离2025年7月1日间隔的最近一次消费时间天数R、客户在2018年4月1日至2025年7月1日之间消费频次F和客户在2018年4月1日至2025年7月1日之间消费金额M（单位：元）的得分排名对客户进行一个综合排名，最终得出一个RFM总评分。a.提取出最近一次消费时间距离当前分析时间的天数R、客户在2018年4月1日至2025年7月1日之间消费频次F和客户在2018年4月1日至2025年7月1日之间消费金额M（单位：元）进行分类，最近一次消费时间间隔最短的客户排在最上面。按照从1-5评分，前20%的客户获得5分，接下来的20%用户获得4分,再下来20%的客户为3分，再下来20% 的客户为2分，最后20% 的客户为1分。 b.根据客户在2018年4月1日至2025年7月1日消费频次F从高到底依次对用户进行分类，前20%的客户在用户活动频率的分数为5，以此类推。 C, 根据客户在2018年4月1日至2025年7月1日消费金额(M)，前20%的客户在消费金额的分数为5，以此类推。消费金额最少的20%客户则分数为1。 RFM得分=0.3*（R得分）+0.3*（F得分）+0.4*（M得分） 评分大于等于4分的为A级客户，大于等于3小于4的为B级客户，大于等于2小于3的为C 级客户，低于2的为D级客户。

Collect data of the Ma'anshan region from the sales record table. Use three indicators for customer analysis: the number of days R since the customer's most recent consumption to July 1, 2025, the customer's consumption frequency F during the period from April 1, 2018 to July 1, 2025, and the customer's total consumption amount M (unit: Yuan). Adopt the RFM model to conduct customer value rating, achieve precise customer operation, and meet the personalized needs of customers with different value levels through value management of local customers. For Class A customers, conduct return visits and maintenance once a month; for Class B customers, once a quarter; for Class C customers, once every six months; and for Class D customers, once a year. In addition, this dataset can provide data support for enterprises with highly overlapping local customer groups to deliver personalized services for customers of different value types. Perform data desensitization, denoising, cleaning, aggregation and analysis on the data collected from the sales record table.

2. Data processing: Conduct a comprehensive ranking of customers using the RFM model combined with the score rankings of the three aforementioned indicators, to finally obtain an overall RFM score.
a. Extract and categorize the three indicators: R (number of days from the customer's most recent consumption to the current analysis date, July 1, 2025), F (consumption frequency during April 1, 2018 to July 1, 2025), and M (total consumption amount during the same period, unit: Yuan). Sort customers in ascending order of R (i.e., customers with the shortest interval since their most recent consumption rank first). Assign scores from 1 to 5: the top 20% of customers receive 5 points, the next 20% receive 4 points, the subsequent 20% receive 3 points, the following 20% receive 2 points, and the last 20% receive 1 point.
b. Categorize customers in descending order of their consumption frequency F during April 1, 2018 to July 1, 2025: the top 20% of customers get 5 points for their consumption frequency, and so on.
c. Categorize customers in descending order of their total consumption amount M during April 1, 2018 to July 1, 2025: the top 20% of customers get 5 points for their consumption amount, and so on. The 20% of customers with the lowest consumption amount get 1 point.
The overall RFM score is calculated as: RFM Score = 0.3 * (R Score) + 0.3 * (F Score) + 0.4 * (M Score). Customers with a score of 4 or higher are classified as Class A customers; those with a score of 3 or higher but less than 4 are Class B; those with a score of 2 or higher but less than 3 are Class C; and those with a score lower than 2 are Class D customers.

搜集汇总

背景与挑战

背景概述

该数据集包含611条马鞍山地区公司平台的客户数据，采用RFM模型评估客户价值，基于最近消费时间、消费频次和消费金额计算得分，将客户分为A、B、C、D四个等级。它主要用于企业精准化运营，通过定期回访和个性化服务优化客户管理，并为其他企业提供数据支持。