深圳地区智能家居咨询客户分级评价数据

采集销售记录表中深圳地区的数据，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，通过对深圳地区客户价值管理，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。数据处理：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。

Data of the Shenzhen region is extracted from the sales record table. Customer value grading is conducted using the RFM model based on three core metrics: Recency (R, time since the customer's last consumption), Frequency (F, number of consumption occurrences within a recent period), and Monetary (M, total consumption amount within a recent period), to enable precise operational management. Through customer value management in the Shenzhen region, personalized demands of customers with different value levels are satisfied, providing data support for personalized services targeting customers of different value types for enterprises in the same industry.

### Data Preprocessing
The collected data from the sales record table is subjected to desensitization, denoising, cleaning, aggregation and analysis.

### Data Scoring & Tiering
A comprehensive customer ranking is generated by combining the RFM model with the score rankings of the three metrics, and a final total RFM score is calculated.
a. For Recency (R): Extract the time interval since each customer's last consumption, sort customers in ascending order (i.e., customers with the shortest interval rank first), then 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. For Frequency (F): Sort customers in descending order of their recent consumption frequency, with the top 20% receiving 5 points, following the same percentile segmentation rule as above.
c. For Monetary (M): Sort customers in descending order of their recent total consumption amount, with the top 20% receiving 5 points and the bottom 20% receiving 1 point, following the same percentile scoring rule.

The total RFM score is calculated as:
RFM Score = 0.3 * R_Score + 0.3 * F_Score + 0.4 * M_Score

Customers are categorized into four value tiers based on their total RFM score:
- Class A customers: Score ≥ 4
- Class B customers: 3 ≤ Score < 4
- Class C customers: 2 ≤ Score < 3
- Class D customers: Score < 2

搜集汇总

数据集介绍

特点

该数据集包含深圳地区智能家居咨询客户的RFM模型评价数据，共825条记录，用于客户价值评级和精准化运营。