广东省客户消费生物基材能力分析评价数据
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统计分析广东省客户购买生物基材的消费记录数据，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，从而为本行业的所有企业针对不同级别客户有针对性的制定广告营销策略。对购买生物基材的广东省客户进行汇总，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：采集各年度公司的销售数据，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年底的间隔天数R，以此为维度对客户进行分类。 3.数据计算：R值得分=（30-R)/3，当R大于30天，则计0分；F值得分=F/当年最高消费频次*10，当年最高消费频次为该年度内客户消费频次的最高值；M值得分=M/当年最高消费总金额*10，当年最高消费总金额为该年度内客户下单总额的最高值；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0.35，0.35，0.3。再根据RFM综合评分对客户进行分类，RFM综合评分大于等于7为A类，RFM综合评分在4到7区间为B类，RFM综合评分小于等于4为C类，通过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，从而本行业的所有企业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 focuses on statistically analyzing the consumption record data of customers in Guangdong Province who purchase bio-based materials. By creating profiles for historical ordering customers, formulating customer tags, and positioning their consumption levels, it provides necessary customer classification data for precision marketing, enabling all enterprises in the industry to formulate targeted advertising and marketing strategies for customers at different levels. First, summarize the data of Guangdong customers who purchased bio-based materials, and classify customers by sorting and clustering their consumption frequency, consumption time interval, and total consumption amount. 1. Data Source: Collect annual sales data of the company, and perform data cleaning and invalid data removal operations on the collected dataset. 2. Data Processing: Adopt the RFM data model. Conduct clustering and aggregation based on customer IDs using three dimensions: consumption frequency (F), total consumption amount (M), and the number of days between the customer's last consumption date and the end of the current year (R), to achieve customer classification. 3. Data Calculation: - R score = (30 - R) / 3; if R exceeds 30 days, the R score is set to 0. - F score = (F / the annual maximum consumption frequency) * 10, where the annual maximum consumption frequency refers to the highest value of customer consumption frequency within the current year. - M score = (M / the annual maximum total consumption amount) * 10, where the annual maximum total consumption amount refers to the highest value of total customer order amounts within the current year. - The RFM comprehensive score is calculated as a*R_score + b*F_score + c*M_score, where the weight coefficients a, b, and c are 0.35, 0.35, and 0.3 respectively. Customers are then classified based on their RFM comprehensive scores: Class A for scores ≥7, Class B for scores ranging from 4 (inclusive) to 7 (exclusive), and Class C for scores ≤4. Through formulating customer tags and positioning customer consumption levels, this dataset provides necessary customer classification data for precision marketing, thereby offering data support for all enterprises in the industry to develop targeted advertising and marketing strategies for customers at different consumption levels.
