天津市花架客户分级评价数据

采集销售记录表中购买花架的数据，通过客户在2025年1月1日距离2025年6月30日间隔的距离距离最近一次消费时间天数R天、客户在2025年1月1日至2025年6月30日之间消费件数F件和客户在2025年1月1日至2025年6月30日之间消费金额M元， 采用 RFM 模型对客户进行价值评级，实现精准化运营，通过对购买花架客户价值管理，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2025年1月1日距离2025年6月30日间隔的距离最近一次消费时间天数R天、客户在2025年1月1日至2025年6月30日之间消费件数F件和客户在2025年1月1日至2025年6月30日之间消费金额M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2025年1月1日距离2025年6月30日之间消费件数F件和客户在2025年1月1日距离2025年6月30日之间消费金额M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2025年1月1日距离2025年6月30日消费件数F件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2025年1月1日距离2025年6月30日消费金额M元，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。

This dataset collects data on flower stand purchases from sales records. Using the RFM model, customer value ratings are conducted based on three metrics: R (number of days since the customer's most recent purchase relative to June 30, 2025, the cutoff of the analysis period from January 1 to June 30, 2025), F (total purchase quantity of the customer during January 1 to June 30, 2025), and M (total consumption amount of the customer during January 1 to June 30, 2025). This enables precise operational management, and by managing the value of flower stand purchasing customers, it meets the personalized needs of customers with different value tiers. Tier A customers receive monthly return visits and maintenance, Tier B customers receive quarterly return visits, Tier C customers receive semi-annual return visits, and Tier D customers receive annual return visits. Additionally, this dataset can provide data support for enterprises with highly overlapping customer groups to deliver personalized services tailored to different customer value types.

The collected data from sales records will undergo desensitization, denoising, cleaning, aggregation and analysis.
2. Data Processing: Conduct a comprehensive ranking of customers using the RFM model combined with the score rankings of R, F and M metrics defined above, to derive the final RFM total score.
a. Extract R (days since most recent purchase relative to June 30, 2025), F (total purchase quantity) and M (total consumption amount) during January 1 to June 30, 2025 for classification. Customers with the shortest interval since their most recent purchase are ranked highest. Score customers from 1 to 5: the top 20% 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. Classify customers based on their total purchase quantity F during January 1 to June 30, 2025 in descending order: the top 20% of customers receive a score of 5 for their purchase frequency, and so on.
c. Classify customers based on their total consumption amount M during January 1 to June 30, 2025: the top 20% of customers receive a score of 5 for their consumption amount, and so forth, with the bottom 20% (lowest consumption amount) receiving a score of 1.
RFM total score = 0.3 * (R score) + 0.3 * (F score) + 0.4 * (M score)
Customers with a total score ≥4 are classified as Tier A customers, those with 3 ≤ score <4 as Tier B, 2 ≤ score <3 as Tier C, and those with score <2 as Tier D.

搜集汇总

背景与挑战

背景概述

该数据集是天津市花架产品的客户分级评价数据，由景宁匠心木制品有限公司基于2025年1月1日至6月30日的销售记录，采用RFM模型对533条客户数据进行价值评级，划分A、B、C、D四个等级，用于精准化运营和客户维护。数据集包含客户名称、销售区域、RFM指标得分等关键字段，更新频次按需，适用于制造业企业优化客户管理策略。