绍兴市建设工程施工客户分级评价数据

通过收集和分析绍兴市客户对建设工程施工服务消费相关数据，使用RFM客户价值模型，了解客户对建设工程施工的购买力水平和消费偏好对客户进行等级评级，实现精准化运营，通过对客户价值管理，满足不同价值客户的个性化需求。对于A等级客户可每月1至2次与之沟通，对于B等级客户可每季度1至2次与之客户沟通，对于C等级客户可每半年1至2次与之沟通。另外可以为本地区客户群体高度重叠企业提供不同等级客户个性化服务的数据支持。1.数据采集：采集绍兴市客户对建设工程施工的相关交易数据。其中，采集数据中“下单时间”为距离统计时间最近的一次订单时间，“订单金额”指的是距离统计时间最近的这次订单金额，“历史服务总次数”“历史服务总金额”指的是历史服务时间段内统计得出的服务次数和服务金额。2.数据处理：对采集到本次订单金额（万元）、历史订单合同总金额（万元）等数据进行分类、合并、累加，便于分析使用，其中客户编号已进行脱敏转换处理。3.算法加工：R评分：根据用户下单时间距离统计时间的天数（D）划分为5个等级: 0≤D≤10为5分，10＜D≤20为4分，20＜D≤30为3分，30＜D≤50为2分，50<D 为1分；F评分：消费频率评分根据历史购买总次数（S）,划分为5个等级: 0<S≤2为1分，2＜S≤5 为2分，5＜S≤10 为3分，10＜S≤15为4分，15< S为5分；M评分：根据历史购买总金额（Z）,划分为5个等级，0<Z≤500为1分，500＜Z≤1500为2分，1500＜Z≤3000为3分，3000＜Z≤5000为4分，5000<Z为5分；RFM综合评分（X）=0.3*R+0.4*F+0.6*M；会员等级分为ABC三级，0≤X≤3为C级，3＜X≤6为B级，6＜X 为A级

This dataset collects and analyzes consumer-related data for construction engineering construction services from customers in Shaoxing City, and adopts the RFM customer value model to evaluate customers' purchasing power levels and consumption preferences for construction engineering, conduct tiered customer rating, achieve precise customer operation, and meet the personalized needs of customers with different value levels through customer value management. For Class A customers, communicate with them 1 to 2 times per month; for Class B customers, communicate 1 to 2 times per quarter; for Class C customers, communicate 1 to 2 times every six months. In addition, it can provide data support for enterprises with highly overlapping local customer groups to deliver personalized services to customers of different tiers.

1. Data Collection: Collect relevant transaction data of Shaoxing customers for construction engineering construction services. In the collected data, "order time" refers to the time of the most recent order relative to the statistical time; "order amount" refers to the amount of the most recent order relative to the statistical time; "total number of historical services" and "total historical service amount" refer to the service times and service amounts calculated within the historical service time period.

2. Data Processing: Classify, merge and accumulate the collected data such as the current order amount (in ten thousand yuan) and the total amount of historical order contracts (in ten thousand yuan) to facilitate subsequent analysis. All customer IDs have been desensitized and converted.

3. Algorithm Processing:
- R Score: Divide the number of days (D) between the customer's order time and the statistical time into 5 levels: 5 points for 0≤D≤10, 4 points for 10<D≤20, 3 points for 20<D≤30, 2 points for 30<D≤50, and 1 point for D>50.
- F Score: The consumption frequency score is divided into 5 levels based on the total number of historical purchases (S): 1 point for 0<S≤2, 2 points for 2<S≤5, 3 points for 5<S≤10, 4 points for 10<S≤15, and 5 points for S>15.
- M Score: Divided into 5 levels based on the total historical purchase amount (Z): 1 point for 0<Z≤500, 2 points for 500<Z≤1500, 3 points for 1500<Z≤3000, 4 points for 3000<Z≤5000, and 5 points for Z>5000.
- RFM Comprehensive Score: The RFM comprehensive score (X) is calculated as X = 0.3*R + 0.4*F + 0.6*M. The customer membership tiers are divided into three levels (A, B, C): Class C for 0≤X≤3, Class B for 3<X≤6, and Class A for X>6.

搜集汇总

背景与挑战

背景概述

该数据集是绍兴市建设工程施工领域的客户分级评价数据，包含511条记录，采用RFM模型对客户进行A、B、C三级评级，基于下单时间、消费频率和总金额等指标实现精准运营。数据来源于企业自行产生，应用场景包括客户价值管理和个性化服务支持，帮助优化客户沟通策略。