美妆行业退款分析数据

此数据通过客户的复购情况分析来验证客户粘性，为企业制定营销策略提供依据。此数据可以帮助企业：1. 客户忠诚度诊断。通过高复购验证客户粘性。2. 新客质量评估。新客复购反应拉新质量。3. 会员运营优化。若会员复购率停滞需升级权益。非会员复购率增长过快可能提示会员特权吸引力不足。4. 资源分配决策。若老客复购率下滑时，需将预算从拉新转向留存活动。高复购率客群可减少促销投入，聚焦服务体验。5. 行业竞争分析。复购率低于行业均值需警惕客户流失风险。6.数据应用：监控服务质量，优化新客体验，评估会员价值，预警忠诚风险，对标行业问题。

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，单位为元。
数据加工：
1. 组成行业的用户样本筛选：用户最大根类目与行业一致;销售金额占比超过全店70%；用户最近12个月有连续的规模交易数据。
2. 订单新老客打标：根据历史全量交易数据计算每个客户的首次购买时间。若客户首次购买时间在统计时间段之前，则该笔订单标记为【老客订单】，否则为【新客订单】。
3.订单会员打标：根据【会员用户关系表】，用订单上的用户和客户信息关联会员状态。关联出客户会员状态为有效，则该笔订单标记为【会员订单】，否则为【非会员订单】。
4. 环比增长=R12指标-R13_24指标
5. 退款率=退款金额 / 订单金额

This dataset validates customer stickiness through analysis of customer repurchase behavior, providing a basis for enterprises to develop marketing strategies. This dataset can help enterprises in the following aspects:
1. Customer loyalty diagnosis: High repurchase rates are used to verify customer stickiness.
2. New customer quality assessment: New customer repurchase behavior reflects the effectiveness of customer acquisition efforts.
3. Membership operation optimization: If the repurchase rate of members stagnates, membership benefits need to be upgraded. An overly rapid growth in the repurchase rate of non-members may indicate insufficient attractiveness of membership privileges.
4. Resource allocation decision-making: When the repurchase rate of existing customers declines, budgets should be shifted from customer acquisition to retention activities. For customer groups with high repurchase rates, promotional investment can be reduced, and focus should be placed on optimizing service experience.
5. Industry competition analysis: If the repurchase rate is lower than the industry average, enterprises should be alert to the risk of customer churn.
6. Data applications: Monitor service quality, optimize new customer experience, evaluate member value, alert loyalty risks, and benchmark against industry issues.

Data Collection:
Omnichannel transaction data and member data are collected and processed through Shuyun's self-developed CRM system. All collected data is fully processed, with the unit being Chinese Yuan (CNY).

Data Processing:
1. Industry user sample screening: Users whose primary root category matches the target industry, whose sales amount accounts for more than 70% of the total store's sales, and who have continuous large-scale transaction data in the most recent 12 months are selected as samples.
2. Order new/returning customer labeling: The first purchase time of each customer is calculated based on full historical transaction data. If the customer's first purchase time is before the statistical period, the order is marked as a [Returning Customer Order]; otherwise, it is marked as a [New Customer Order].
3. Order member labeling: According to the [Member-User Relationship Table], the membership status is associated with the user and customer information on the order. If the customer's membership status is confirmed valid after association, the order is marked as a [Member Order]; otherwise, it is marked as a [Non-Member Order].
4. Month-on-month growth = R12 indicator - R13_24 indicator
5. Refund rate = refund amount / order total amount

搜集汇总

背景与挑战

背景概述

该数据集是美妆行业的退款分析数据，包含2024年3月至2025年2月的订单金额、退款金额及退款率等指标，细分新客、老客、会员和非会员群体。数据用于分析客户复购行为和退款趋势，支持企业优化营销策略和会员运营，每月更新一次。