邯郸市无人机客户分级评价数据
收藏资源简介：
通过收集和分析邯郸市客户对无人机消费相关数据，使用RFM客户价值模型，了解客户对无人机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：采集邯郸市客户对无人机的相关交易数据。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，“历史购买总次数”“历史购买总金额”指的是历史服务时间段内统计得出的购买次数和购买金额。2.数据处理：对采集到本次订单金额（万元）、历史订单总金额（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≤30为1分，30＜Z≤50为2分，50＜Z≤80为3分，80＜Z≤100为4分，100<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 is developed by collecting and analyzing consumer-related data of customers in Handan City for unmanned aerial vehicles (UAVs). The RFM customer value model is adopted to understand customers' purchasing power and consumption preferences, conduct grade rating on customers, realize precise operation, and meet the personalized demands of customers with different values. 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 half a year. Additionally, it can provide data support for enterprises with highly overlapping local customer groups to offer personalized services for customers of different grades. 1. Data Collection: Collect relevant transaction data of UAVs from customers in Handan City. Specifically, the "order time" in the collected data refers to the time of the most recent order relative to the statistical time; the "order amount" refers to the amount of the most recent order relative to the statistical time; "total historical purchase times" and "total historical purchase amount" refer to the total purchase times and purchase amount calculated within the historical service period. 2. Data Processing: Classify, merge and accumulate the collected data such as the current order amount (in ten thousand yuan) and total historical order amount (in ten thousand yuan) to facilitate analysis. Note that customer IDs have been desensitized and converted. 3. Algorithm Processing: - R Score: Divide into 5 levels based on the number of days (D) between the user's order time and the statistical time: 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: Divide the consumption frequency score into 5 levels based on the total historical purchase times (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: Divide into 5 levels based on the total historical purchase amount (Z): 1 point for 0<Z≤30, 2 points for 30<Z≤50, 3 points for 50<Z≤80, 4 points for 80<Z≤100, and 5 points for Z>100. - RFM Comprehensive Score (X) = 0.3*R + 0.4*F + 0.6*M. - Member levels are divided into three grades: Class C for 0≤X≤3, Class B for 3<X≤6, and Class A for X>6.
