重庆地区元宇宙名片客户分级评价数据

采集管理后台中重庆地区的数据，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，通过对重庆地区客户价值管理，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 from the Chongqing region via the administration backend. It applies the RFM model to evaluate customer value based on three core metrics: Recency (R, time elapsed since the customer's most recent consumption), Frequency (F, total consumption frequency over a recent period), and Monetary (M, total consumption amount over a recent period), aiming to enable precise operational management. By managing customer value in the Chongqing region, it meets the personalized demands of customers across different value tiers, and provides data support for personalized services targeting customers of various value types for enterprises in the same industry. 1. Data Preprocessing: The data collected from the administration backend will undergo desensitization, noise reduction, cleaning, aggregation and analysis. 2. RFM-based Customer Scoring: Utilize the RFM model combined with the score rankings of the three aforementioned metrics to conduct a comprehensive ranking of customers, and finally calculate the total RFM score. a. Extract the three metrics (R, F, M) for classification. Rank customers in ascending order of the time interval since their last purchase (i.e., customers with the shortest interval rank first). Assign scores from 1 to 5 following the percentile rule: the top 20% of customers receive 5 points, the next 20% get 4 points, the subsequent 20% get 3 points, the next 20% get 2 points, and the last 20% get 1 point. b. Classify customers based on their recent consumption frequency (F) in descending order. The top 20% of customers get 5 points for their activity frequency, and the remaining customers are assigned scores per the same percentile-based standard. c. Based on the recent consumption amount (M), the top 20% of customers receive 5 points, while the bottom 20% get 1 point, with the rest assigned scores following the same rule. The total RFM score is calculated as: Total RFM Score = 0.3 * R_score + 0.3 * F_score + 0.4 * M_score. Customers are classified into four tiers: Grade A clients with a total score ≥ 4; Grade B clients with 3 ≤ score < 4; Grade C clients with 2 ≤ score < 3; and Grade D clients with a score < 2.

搜集汇总

数据集介绍

特点

该数据集包含715条重庆地区元宇宙名片客户的分级评价数据，采用RFM模型（基于最近消费时间、频次和金额）对客户进行价值评级，应用于精准化运营和个性化服务支持。数据格式为xlsx，按需更新。