杭州市新媒体推广服务客户分级评价数据

通过收集和分析杭州市客户对新媒体推广服务消费相关数据，使用RFM客户价值模型，了解客户对新媒体推广服务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：采集杭州市客户对新媒体推广服务的相关交易数据。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≤3为1分，3＜Z≤8为2分，8＜Z≤15为3分，15＜Z≤30为4分，30<Z为5分；RFM综合评分（X）=0.3*R+0.4*F+0.6*M；客户等级分为ABC三级，0≤X≤3为C级，3＜X≤6为B级，6＜X 为A级This dataset is constructed by collecting and analyzing consumption data of customers in Hangzhou related to new media promotion services, and adopting the RFM Customer Value Model to conduct grade rating on customers based on their purchasing power and consumption preferences for new media promotion services, so as to realize precise operation and meet the personalized demands of customers with different values. For Grade A customers, communicate with them 1 to 2 times per month; for Grade B customers, communicate with them 1 to 2 times per quarter; for Grade C customers, communicate with them 1 to 2 times every six months. Additionally, it can provide data support for local enterprises with highly overlapping customer groups to deliver personalized services for customers of different grades. 1. Data Collection: Collect relevant transaction data of Hangzhou customers for new media promotion services. In the collected data, "order placement time" refers to the time of the latest order relative to the statistical time; "order amount" refers to the amount of the latest order relative to the statistical time; "total historical purchase times" and "total historical purchase amount" refer to the total number of purchases and total purchase amount calculated within the statistical service time period. 2. Data Processing: Classify, merge and accumulate the collected data such as the current order amount (ten thousand yuan) and total historical order amount (ten thousand yuan) to facilitate subsequent analysis. The customer IDs have been processed via desensitization conversion. 3. Algorithm Processing: Recency Score (R): Divided into 5 levels based on the number of days (D) between the customer's latest order placement 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, 1 point for D>50. Frequency Score (F): Divided into 5 levels based on 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, 5 points for S>15. Monetary Score (M): Divided into 5 levels based on total historical purchase amount (Z) (unit: ten thousand yuan): 1 point for 0<Z≤3, 2 points for 3<Z≤8, 3 points for 8<Z≤15, 4 points for 15<Z≤30, 5 points for Z>30. RFM Comprehensive Score (X) = 0.3*R + 0.4*F + 0.6*M; Customer levels are divided into three grades A, B and C: Grade C for 0≤X≤3, Grade B for 3<X≤6, Grade A for X>6.

搜集汇总

背景与挑战

背景概述

该数据集包含510条杭州市新媒体推广服务客户数据，采用RFM模型对客户进行分级评价，包括R、F、M评分和客户等级字段，用于精准运营和个性化服务支持，数据按需更新。