昆明市日化用品类客户分级评价数据

采集昆明市日化用品类客户的最近一次消费时间（R）、最近一段时间消费频次(F)、最近一段时间消费金额(M)，采用RFM模型对客户进行价值评级，用RFM分析方法把客户分为ABCD四级，对细分过后的不同客户采取相应营销策略，进行精准有效的运营。通过对客户进行分级管理，满足不同等级客户的个性化需求，并为同行业企业管理不同等级的客户，实现精准个性化服务提供数据支持。 1、数据处理：对从昆明市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模型结合客户最近一次消费时间（R）、客户最近一段时间消费频次(F)和客户最近一段时间消费金额(M)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.提取出客户最近一次消费时间（R）、客户最近一段时间消费频次(F)和客户最近一段时间消费金额(M)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.根据客户最近一段时间消费频次(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, 根据客户最近一段时间消费金额(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。

This dataset collects Recency (R, the time elapsed since the customer's last purchase), Frequency (F, the number of purchases within a specified recent period), and Monetary value (M, the total consumption amount within a specified recent period) of customers in the daily chemical product industry in Kunming. The RFM model is applied to conduct customer value grading, and customers are divided into four tiers (A, B, C, D) via RFM analysis. Corresponding marketing strategies are adopted for each segmented customer group to enable precise and efficient operations. Through hierarchical customer management, personalized demands of customers at different tiers are satisfied, providing data support for peer enterprises to manage customers of various tiers and deliver precise personalized services.

1. Data Processing: Desensitize, denoise, clean, aggregate and analyze the data collected from Kunming.
2. Data Refinement: Combine the RFM model with the score rankings of the customer's last purchase time (R), recent purchase frequency (F) and recent consumption amount (M) to conduct a comprehensive ranking of customers, and finally obtain an overall RFM score.
a. Extract the Recency (R), Frequency (F) and Monetary value (M) indicators of customers for classification. Customers with the shortest time interval since their last purchase are ranked first. A 1-5 scoring framework is adopted: the top 20% of customers are awarded 5 points, the next 20% get 4 points, the subsequent 20% get 3 points, the following 20% get 2 points, and the last 20% get 1 point.
b. Classify customers in descending order based on their recent purchase frequency (F). The top 20% of customers receive 5 points for their activity frequency, and the rest are scored following the same rule.
c. For customers' recent consumption amount (M), the top 20% get 5 points, and so on. The 20% of customers with the lowest consumption amount are awarded 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 an overall RFM score ≥4 are classified as Tier A customers, those with a score of ≥3 and <4 as Tier B, those with a score of ≥2 and <3 as Tier C, and those with a score below 2 as Tier D.