云南地区童装校服客户价值评价数据

通过收集和分析各区域客户对童装校服产品消费相关数据，对历史下单客户建立画像，对客户进行标签制定，定位客户消费级别，为精准营销提供必要的客户分类数据，针对不同级别客户有针对性的制定广告营销策略提供数据支持。例如对于A等级客户可每周1至2次与之沟通及消息推送，店庆等特定日期赠送大礼包、优惠券等；对于B等级客户可每月1至2次与之客户沟通，店庆等特定日期赠送优惠券等；对于C等级客户可每季度1至2次与之沟通，从而制定更精准的生产营销策略，同时也为本行业的所有企业制定生产策略提供依据。1.数据采集：采集期间为分析时间所处月份的前12个月，截取的第一个月从该月第一天起，最后一个月为该月最后一天截止，例如：分析时间为2025年11月24日，则采集2024年11月1日至2025年10月31日期间各个客户对童装校服产品的相关交易数据。 2.数据处理：对采集到下单情况、付款金额（元）等数据进行分类、合并、累加，便于分析使用。 3.算法加工：R评分根据用户最新下单时间距离分析时间的间隔天数D,划分为5个等级: 0≤D≤30为5分，30＜D≤60为4分，60＜D≤90为3分，90＜D≤120为2分，120<D 为1分； F评分根据购买频率S,划分为5个等级: 0<S≤2为1分，2＜S≤4 为2分，4＜S≤7 为3分，7＜S≤10为4分，10< S为5分； M评分根据付款总额Z,划分为5个等级，0<Z≤500为1分，500＜Z≤1000 为2分，1000＜Z≤2000 为3分，2000＜Z≤3000为4分，3000< Z为5分；RFM综合评分（X）=a*R+b*F+c*M，a，b，c为权重系数分别为0.3，0.3，0.4。客户等级分为ABC三级，0≤X≤2为C级，2＜X≤3.5为B级，3.5＜X 为A级。

This dataset is constructed by collecting and analyzing customer consumption data related to children's school uniform products across various regions. It builds customer profiles for historical ordering customers, develops customer tags, positions customer consumption levels, provides necessary customer classification data for precision marketing, and supports the development of targeted advertising and marketing strategies for customers at different levels. Additionally, it helps formulate more accurate production and marketing strategies, and offers a reference for all enterprises in this industry to develop production strategies. For example, Grade A customers can be communicated with and sent messages 1 to 2 times per week, and receive gift packages and coupons on specific dates such as store anniversaries; Grade B customers can be communicated with 1 to 2 times per month and receive coupons on specific dates such as store anniversaries; Grade C customers can be communicated with 1 to 2 times per quarter.

1. Data Collection: The data collection period covers the preceding 12 months of the month in which the analysis is conducted, starting from the first day of the first month of this period and ending on the last day of the last month. For instance, if the analysis is conducted on November 24, 2025, the relevant transaction data of each customer for children's school uniform products from November 1, 2024 to October 31, 2025 will be collected.

2. Data Processing: Classify, merge and accumulate the collected data such as order status and payment amount (yuan) to facilitate subsequent analysis.

3. Algorithm Processing:
The R score is divided into 5 levels based on the number of days D between the user's latest order time and the analysis time: 5 points for 0≤D≤30, 4 points for 30<D≤60, 3 points for 60<D≤90, 2 points for 90<D≤120, and 1 point for D>120.
The F score is divided into 5 levels based on the purchase frequency S: 1 point for 0<S≤2, 2 points for 2<S≤4, 3 points for 4<S≤7, 4 points for 7<S≤10, and 5 points for S>10.
The M score is divided into 5 levels based on the total payment Z: 1 point for 0<Z≤500, 2 points for 500<Z≤1000, 3 points for 1000<Z≤2000, 4 points for 2000<Z≤3000, and 5 points for Z>3000.
The comprehensive RFM score (X) is calculated as X = a*R + b*F + c*M, where the weight coefficients a, b, and c are 0.3, 0.3, and 0.4 respectively. Customer levels are divided into three grades A, B and C: Grade C for 0≤X≤2, Grade B for 2<X≤3.5, and Grade A for X>3.5.

搜集汇总

背景与挑战

背景概述

该数据集专注于云南地区童装校服客户的消费行为分析，包含566条记录，通过RFM模型（基于最近购买时间、购买频率和消费金额）对客户进行价值评估，将客户划分为A、B、C三个等级。数据集旨在为精准营销提供支持，帮助制定针对不同客户级别的沟通策略和广告营销方案，从而优化生产营销决策。