杭州市舟山旅游客户分级评价数据
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通过收集和分析杭州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：采集杭州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 related to Zhoushan tourism products (including scenic spot tickets, ferry tickets, intercity bus tickets, flight tickets, etc.) from tourists in Hangzhou on the Enterprise Cloud Merchant Platform. The RFM customer value model is employed to investigate tourists' purchasing power and consumption preferences for Zhoushan tourism, perform grade classification on tourists, and enable precise operational management. Through customer value management, personalized needs of customers with different value tiers are met. Specifically, preferential information can be sent to Grade A customers for communication 1 to 2 times per month; tourism-related information can be distributed to Grade B customers 1 to 2 times per quarter; and promotional activity information can be pushed to Grade C customers 1 to 2 times every six months. Additionally, data support for personalized services can be provided for local tourism-related enterprises in Zhoushan, such as scenic spots, hotels, travel agencies, transportation companies, etc. 1. Data Collection: Collect transaction data of Hangzhou tourists' purchases of Zhoushan tourism products (including scenic spot tickets, ferry tickets, intercity bus tickets, flight tickets, and other related products) on the Enterprise Cloud Merchant Platform. In the collected data, "order placement time" refers to the time of the most recent order relative to the cutoff date (2025/8/31); "order amount" refers to the amount of this most recent order; "total historical purchase times" and "total historical purchase amount" are the total number of purchases and total purchase amount calculated within the historical service period (January 1, 2024 to August 31, 2025). 2. Data Processing: Classify, merge, and aggregate the collected data such as the current order amount (in RMB) and total historical purchase amount (in RMB) to facilitate analysis. Note that customer IDs have been processed via desensitization transformation. 3. Algorithm Processing: - R (Recency) Score: Divide the number of days (D) between the user's order placement time and the cutoff date 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 (Frequency) Score: Divide the total historical purchase times (S) into 5 levels based on consumption frequency: 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 (Monetary) Score: Divide the total historical purchase amount (Z, unit: RMB) into 5 levels: 1 point for 0 < Z ≤ 5000, 2 points for 5000 < Z ≤ 10000, 3 points for 10000 < Z ≤ 15000, 4 points for 15000 < Z ≤ 30000, and 5 points for Z > 30000. - Comprehensive RFM Score (X) = 0.3×R + 0.4×F + 0.6×M. - Customer levels are divided into three tiers: Grade C for 0 ≤ X ≤ 3, Grade B for 3 < X ≤ 6, and Grade A for X > 6.
