大理地区元宇宙名片客户分级评价数据

采集管理后台中大理地区的数据，通过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，实现精准化运营，通过对大理地区客户价值管理，满足不同价值客户的个性化需求。并为同行业企业不同价值类型的客户个性化服务提供数据支持。1、数据处理：对从管理后台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 data of the Dali region from the collection and management backend. It adopts the RFM model to conduct value rating on customers based on their most recent consumption time (R), recent consumption frequency (F) and recent total consumption amount (M), so as to achieve precise operation. By managing the customer value in the Dali region, it meets the personalized demands of customers with different value levels, and provides data support for personalized services targeting customers of different value types for enterprises in the same industry.

1. Data Preprocessing: Desensitize, denoise, clean, aggregate and analyze the data collected from the management backend.
2. Data Refinement & Scoring: Use the RFM model combined with the score rankings of the customer's most recent consumption time (R), recent consumption frequency (F) and recent total consumption amount (M) to conduct a comprehensive ranking of customers, and finally obtain the overall RFM score.
a. Extract the customer's most recent consumption time (R), recent consumption frequency (F) and recent total consumption amount (M) for classification. Customers with the shortest interval since their last consumption are ranked first. The scoring is carried out on a scale of 1 to 5: the top 20% of customers get 5 points, the next 20% get 4 points, the following 20% get 3 points, the next 20% get 2 points, and the last 20% get 1 point.
b. Classify customers in descending order based on their recent consumption frequency (F). The top 20% of customers get 5 points for their activity frequency, and so on.
c. Based on the customer's recent total consumption amount (M), 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 are categorized into four levels: Grade A (score ≥ 4), Grade B (3 ≤ score < 4), Grade C (2 ≤ score < 3), and Grade D (score < 2).