配送全国区域内的各个企业层级数据

通过计算本公司与全国区域内的不同企业的配送消费信息，对不同的企业按照RFM模型进行分层，本行业所有配送公司可对不同层级的企业采取不同的运营策略。其次，本数据还能为配送行业的相关企业如物流公司等提供整体性参考，从而有效洞察市场趋势，更好地做出科学的营销决策。1、数据采集：导出本公司与全国区域内的不同企业的配送消费信息。2、数据处理：以企业编号作为唯一标识，对数据进行清洗、去除无效数据和极限数据等操作。3、数据加工：通过LOOKUP函数计算出企业最近一次配送距离当月月底的天数，COUNTIF函数计算当月配送次数，SUMIF函数计算当月配送总金额，最近一次配送距离当月月底的天数大于或者等于当月平均配送间隔天数则R定档值为1，反之R定档值为0，当月配送次数大于或者等于当月平均配送次数则F定档值为1，反之F定档值为0，当月配送总金额大于或者等于当月配送平均金额则M定档值为1，反之M定档值为0，再根据RFM模型分层规则按RFM值将企业分为8个层级，即分为重要价值客户(RFM为111)、重要保持客户(RFM为101)、重要发展客户(RFM为011)、重要挽留客户(RFM为001)、一般价值客户(RFM为110)、一般保持客户(RFM为100)、一般发展客户(RFM为010)和一般挽留客户(RFM为000)。4、数据应用：通过对企业进行分层管理，所有配送公司可对不同层级的企业定制不同的运营策略。

This dataset is developed by analyzing delivery consumption data between our company and various enterprises nationwide to stratify enterprises using the RFM model, enabling all delivery companies in the industry to adopt tailored operational strategies for enterprises of different tiers. Furthermore, this dataset can provide holistic references for relevant enterprises in the delivery industry, such as logistics companies, helping them gain actionable insights into market trends and make more evidence-based marketing decisions.
1. Data Collection: Export delivery consumption data between our company and various enterprises across the nation.
2. Data Preprocessing: Take the enterprise ID as the unique identifier, clean the dataset, and remove invalid and outlier data, along with other relevant processing operations.
3. Data Calculation and Stratification: Calculate the number of days between the most recent delivery and the end of the current month using the LOOKUP function; use the COUNTIF function to calculate the monthly delivery count; use the SUMIF function to calculate the total monthly delivery amount. Then assign the R score: set R=1 if the number of days from the last delivery to the end of the current month is greater than or equal to the average delivery interval days of the current month, otherwise set R=0. Assign the F score: set F=1 if the monthly delivery count is greater than or equal to the average monthly delivery frequency, otherwise set F=0. Assign the M score: set M=1 if the total monthly delivery amount is greater than or equal to the average monthly delivery amount, otherwise set M=0. Subsequently, stratify enterprises into 8 tiers per the RFM model stratification rules based on their combined RFM values: Important Value Customers (RFM=111), Important Retained Customers (RFM=101), Important Developmental Customers (RFM=011), Key Retention Candidates (RFM=001), General Value Customers (RFM=110), General Retained Customers (RFM=100), General Developmental Customers (RFM=010), and General Retention Candidates (RFM=000).
4. Data Application: Through stratified enterprise management, all delivery companies can formulate customized operational strategies for enterprises of different tiers.