上海市舟山旅游客户分级评价数据

通过收集和分析上海市游客在企业云商平台上对舟山旅游产品（景区门票、船票、大巴票、机票等）消费相关数据，使用RFM客户价值模型，了解游客对舟山旅游的购买力水平和消费偏好，对游客进行等级评级，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次推送优惠信息与之沟通，对于B等级客户可每季度1至2次发送旅游资讯与之沟通，对于C等级客户可每半年1至2次推送活动信息与之沟通。另外可以为舟山本地旅游相关企业（景区、酒店、旅行社、交通公司等）提供不同等级客户个性化服务的数据支持。1.数据采集：采集上海市游客在企业云商平台上对舟山旅游产品（景区门票、船票、大巴票、机票等产品）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（2025/8/31）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（2024/1/1-2025/8/31）内统计得出的购买次数和购买金额。 2.数据处理：对采集到的本次订单金额（元）、历史购买总金额（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，单位：元），划分为5个等级：0<Z≤5000为1分，5000＜Z≤10000为2分，10000＜Z≤15000为3分，15000＜Z≤30000为4分，30000<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 transaction data of Shanghai tourists on the Enterprise Cloud Merchant Platform regarding Zhoushan tourism products (including scenic spot tickets, ferry tickets, coach tickets, flight tickets, etc.). The RFM customer value model is applied to assess the purchasing power and consumption preferences of tourists towards Zhoushan tourism, grade tourists to achieve precise operation, and meet personalized demands of customers with different value tiers. Specifically, Level A customers will receive 1 to 2 promotional messages per month for communication, Level B customers will be sent 1 to 2 tourism information materials every quarter, and Level C customers will get 1 to 2 event promotion information every six months. Additionally, this dataset can provide data support for personalized services targeting customers of different tiers for local tourism-related enterprises in Zhoushan (such as scenic spots, hotels, travel agencies, transportation companies, etc.). 1. Data Collection: Collect transaction data related to Zhoushan tourism products (scenic spot tickets, ferry tickets, coach tickets, flight tickets, etc.) of Shanghai tourists on the Enterprise Cloud Merchant Platform. Among them, the "order time" in the collected data refers to the timestamp of the most recent order relative to the statistical cutoff time (2025/8/31); the "order amount" refers to the transaction amount of the most recent order relative to the statistical cutoff time; "total historical purchase times" and "total historical purchase amount" refer to the total number of purchases and total transaction amount counted within the historical service period (2024/1/1 - 2025/8/31). 2. Data Processing: Classify, merge and accumulate the collected data such as the current order amount (in CNY) and total historical purchase amount (in CNY) to facilitate subsequent analysis. All customer IDs have been desensitized and converted. 3. Algorithm Processing: - R Score: The recency score is divided into 5 levels based on the number of days (D) between the user's order timestamp and the statistical cutoff 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. - F Score: The frequency score is divided 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, 5 points for S>15. - M Score: The monetary score is divided into 5 levels based on the total historical purchase amount (Z, unit: CNY): 1 point for 0<Z≤5000, 2 points for 5000<Z≤10000, 3 points for 10000<Z≤15000, 4 points for 15000<Z≤30000, 5 points for Z>30000. - RFM Comprehensive Score (X) = 0.3×R + 0.4×F + 0.6×M. - Customer levels are divided into three tiers: Level C for 0≤X≤3, Level B for 3<X≤6, and Level A for X>6.

搜集汇总

背景与挑战

背景概述

该数据集聚焦上海市游客对舟山旅游产品的消费行为，包含1301条记录，每日更新，采用RFM客户价值模型（基于最近消费时间、频率和金额）进行客户分级评价，划分为A、B、C三个等级，旨在实现精准运营和个性化服务支持。