山西省抖音平台食品类客户分级评价数据

采集山西省抖音平台客户消费行为数据，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，通过对山西省抖音平台客户价值管理，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：对采集到的数据进行降噪、清洗、脱敏、聚集、分析。
2、数据加工：运用RFM模型结合用户的最近一次活动（R）、用户活动频率（F）和消费金额（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)，将用户按照最近一次活动（R）进行分类，最近一次活动时间间隔最短的用户排在最上面。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.根据客户活动频率（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.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=（R）得分*0.3+（F）得分*0.3+（M）得分*0.4。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。
3、通过对客户的分级管理，为不同价值类型的客户个性化服务提供数据支持。

This dataset collects consumer behavior data of customers on the Douyin platform in Shanxi Province. The RFM model, which takes into account three core metrics: Recency (R: time elapsed since the customer's last consumption activity), Frequency (F: total number of consumption activities within a recent period), and Monetary (M: total consumption amount within a recent period), is adopted to conduct customer value rating, so as to realize precise operational management. Through customer value management on the Douyin platform of Shanxi Province, the dataset meets the personalized demands of customers with different value levels, and provides data support for enterprises in the same industry to deliver personalized services for customers of different value types.

1. Data Processing: Noise reduction, data cleaning, data anonymization, data aggregation and data analysis are performed on the collected raw data.

2. Data Enrichment and Scoring: The RFM model is applied to generate a comprehensive customer ranking and final overall RFM score, based on the score rankings of the customer's last consumption activity (R), activity frequency (F) and consumption amount (M).
a. Extract the three core metrics of Recency (R), Frequency (F) and Monetary (M). First, classify users according to their last consumption activity time (R): users with the shortest time interval since their last activity are ranked highest. Score users on a 1-5 scale: the top 20% of customers receive 5 points, the next 20% receive 4 points, the subsequent 20% receive 3 points, the next 20% receive 2 points, and the last 20% receive 1 point.
b. Classify users in descending order of their activity frequency (F): the top 20% of customers are assigned 5 points for their activity frequency score, and the remaining users are assigned scores following the same percentile-based rule.
c. For the consumption amount (M) metric: the top 20% of customers are assigned 5 points for their consumption amount score, while the 20% of customers with the lowest consumption amount receive 1 point, with other groups assigned scores per the same percentile standard.
The overall RFM score is calculated as: RFM Score = 0.3 * R Score + 0.3 * F Score + 0.4 * M Score. Customers with a score greater than or equal to 4 are classified as Level A customers, those with a score between 3 (inclusive) and 4 (exclusive) as Level B customers, those with a score between 2 (inclusive) and 3 (exclusive) as Level C customers, and those with a score lower than 2 as Level D customers.

3. Hierarchical Customer Management: The dataset provides data support for personalized service provision targeting customers of different value types through classified customer management.

搜集汇总

数据集介绍

特点

数据集包含山西省抖音平台食品类客户的消费行为数据，使用RFM模型对客户进行价值评级，每月更新1588条记录，用于精准化运营和客户价值管理。