美妆行业关键客户复购分析数据

此数据通过对一定规模美妆行业关键客户复购数据进行分析，帮助企业：1. 客户流失预警与返回。前5%客户复购率环比负增长，可能是大客户流失前兆，需立刻排查原因。前10%~20%客户复购率下降，反映中高价值客户粘性降低，需优化复购激励 ; 2. 客户忠诚度分析。若前5%客户复购率 远高于 前10%~20%，反映品牌对顶级客户依赖度高，需加强中腰部客户的留存策略。若各层级复购率差距小，说明客户忠诚度分布均匀，品牌健康度较好 ; 3. 营销效果评估 ; 4.数据应用：
监控复购率变化，预警流失风险，优化客户分层策略。数据采集：
通过数云自研CRM系统采集全渠道交易数据、会员数据并进行加工。获取数据完整进行加工，单位为人。
数据加工：
1. 复购率=复购客户数 / 客户数
2. 环比增长=R12指标-R13_24指标
3.R12指标：指最近12个月的指标数据；R13_24指标：指往前13-24个月的指标数据。
4.数据结构中第15-17项复购率指代的是R12; 第18-20项复购率环比增长指代的是R13_24

This dataset is derived from the analysis of repurchase data of key customers in the beauty industry at a certain scale, aiming to help enterprises in the following aspects:
1. Customer churn warning and win-back: If the repurchase rate of the top 5% of customers experiences month-on-month negative growth, it may be a precursor to the churn of large-value key customers, requiring immediate investigation into the underlying causes. The decline in repurchase rate of the top 10% to 20% of customers reflects reduced loyalty among mid-to-high-value customers, necessitating optimization of repurchase incentive strategies.
2. Customer loyalty analysis: If the repurchase rate of the top 5% of customers is significantly higher than that of the top 10% to 20% of customers, it indicates that the brand has high dependence on top-tier customers, and retention strategies for mid-tier customers need to be strengthened. If the gap in repurchase rates across all customer tiers is small, it means that customer loyalty is evenly distributed, and the brand has good operational health.
3. Marketing effect evaluation
4. Data application: Monitor changes in repurchase rate to warn of churn risks and optimize customer stratification strategies.

Data Collection: Full-channel transaction data and membership data are collected and processed through Shuyun's self-developed CRM system. The data is fully processed, with the unit being individual customers.

Data Processing:
1. Repurchase Rate = Number of repurchasing customers / Total number of customers
2. Month-on-Month Growth = R12 Indicator - R13_24 Indicator
3. R12 Indicator: Refers to the indicator data of the most recent 12 months; R13_24 Indicator: Refers to the indicator data from the 13th to 24th months prior to the current statistical period.
4. The 15th to 17th items in the data structure represent the repurchase rate corresponding to R12; the 18th to 20th items represent the month-on-month growth of repurchase rate corresponding to R13_24.