饺子盒类客户消费能力分析评价数据

统计分析公司销售平台购买饺子盒类客户消费记录数据，通过对历史下单客户建立画像，对客户进行标签制定，定位客户消费级别，为精准营销提供必要的客户分类数据，针对不同级别客户有针对性的制定广告营销策略提供数据支持。 客户分类的算法规则采用RFM数据模型排序、聚类的方法，对平台上下单饺子盒的客户进行汇总，通过对客户的消费频次和消费时间间隔、消费总金额的排序、聚类，对客户进行分类。 1.数据来源：采集公司网络平台的销售数据，对数据进行清洗、去除无效数据等操作。 2.数据处理：采用RFM数据模型。通过对客户ID的聚类汇总消费频次F、消费总金额M、最近一次消费时间距离当前天数R，以此为维度对客户进行分类。 3.数据计算：R值得分=（30-R)/30*10，当R大于30天，则计0分；M值得分=M/最高消费总金额*10，最高消费总金额为采集时间段内客户下单总额的最高值；F值得分=F/最高消费频次*10，最高消费频次为采集时间段内客户消费频次的最高值；RFM综合评分=a*R值得分+b*F值得分+c*M值得分，a，b，c为权重系数分别为0.3，0.3，0.4。再根据RFM综合评分对客户进行分类，RFM综合评分≥7，为A类，RFM综合评分≥4，分为B类，RFM综合评分＜4，为C类，对客户进行标签制定，定位客户消费级别，为精准营销提供必要的客户分类数据，针对不同级别客户有针对性的制定广告营销策略提供数据支持。

This dataset is derived from the customer consumption record data of dumpling box products on the sales platform of a statistical analysis company. The purpose of this dataset is to establish customer profiles for historical ordering customers, formulate customer labels, classify customer consumption levels, provide necessary customer classification data for precise marketing, and offer data support for developing targeted advertising and marketing strategies for customers of different tiers. The customer classification algorithm adopts the sorting and clustering method based on the RFM data model. First, summarize the customers who placed orders for dumpling boxes on the platform, then classify customers by sorting and clustering based on their consumption frequency, consumption time interval, and total consumption amount. The specific details are as follows:
1. Data Source: Collect sales data from the company's online platform, and perform data cleaning and invalid data removal operations.
2. Data Processing: Adopt the RFM data model. Take customer ID as the aggregation dimension to summarize three indicators: consumption frequency (F), total consumption amount (M), and the number of days from the last consumption date to the current date (R), and classify customers based on these three dimensions.
3. Data Calculation:
- R score = (30 - R) / 30 * 10; if R > 30 days, the score is set to 0.
- M score = M / maximum total consumption amount * 10, where the maximum total consumption amount refers to the highest total order amount of all customers during the data collection period.
- F score = F / maximum consumption frequency * 10, where the maximum consumption frequency refers to the highest consumption frequency of all customers during the data collection period.
- The overall RFM score = a * R_score + b * F_score + c * M_score, where the weight coefficients a, b, and c are 0.3, 0.3, and 0.4 respectively.
Finally, classify customers based on the overall RFM score: customers with an overall RFM score ≥ 7 are classified as "Class A", those with a score ≥ 4 as "Class B", and those with a score < 4 as "Class C". This process is used to formulate customer labels and locate their consumption levels, providing necessary customer classification data for precise marketing and data support for developing targeted advertising and marketing strategies for customers of different levels.

搜集汇总

数据集介绍

特点

该数据集包含2612条饺子盒类客户的消费记录，采用RFM模型对客户进行分类，用于精准营销和客户分类分析。