美妆行业客户复购情况分析数据

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：诊断客户忠诚度，评估新客质量，优化会员运营，调整资源分配，对标行业竞争。

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，单位为个。
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. 交易数：订单合并，统计客户购买次数
6. R12（R13_24）客户数：最近12个月（往前13-24个月）客户ID去重计数。
7. R12（R13_24）复购客户数：最近12个月（往前13-24个月）交易数大于等于2客户ID去重计数。
复购率=复购客户数 / 客户数

This dataset verifies 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: Verify customer stickiness through high repurchase rates.
2. New customer quality assessment: The repurchase behavior of new customers reflects the quality of customer acquisition efforts.
3. Member operation optimization: If the repurchase rate of members stagnates, it is necessary to upgrade member benefits. If the repurchase rate of non-members grows too rapidly, it may indicate that the appeal of member privileges is insufficient.
4. Resource allocation decision-making: When the repurchase rate of returning customers declines, it is necessary to shift the budget from customer acquisition to retention activities. For customer groups with high repurchase rates, promotional investment can be reduced, and focus should be placed on service experience.
5. Industry competition analysis: If the repurchase rate is lower than the industry average, it is necessary to be alert to the risk of customer churn.
6. Data applications: Diagnose customer loyalty, assess new customer quality, optimize member operations, adjust resource allocation, and benchmark against industry competition.

The data is collected and processed through the self-developed CRM system of Shuyun, including omni-channel transaction data and member data, with the unit of "individual".

Data processing steps:
1. User sample screening for industry composition: Users whose primary root category matches the target industry; whose sales amount accounts for more than 70% of the total store sales; and who have continuous large-scale transaction data in the most recent 12 months.
2. New/returning customer labeling for orders: Calculate the first purchase time of each customer based on full historical transaction data. If the customer's first purchase time was before the statistical period, the order is marked as [returning customer order]; otherwise, it is marked as [new customer order].
3. Member/non-member labeling for orders: Associate the membership status with the user and customer information on the order via the [Member User Relationship Table]. If the customer's membership status is valid, the order is marked as [member order]; otherwise, it is marked as [non-member order].
4. Month-on-month growth = R12 indicator - R13_24 indicator
5. Transaction count: Merge orders and count the number of customer purchase times.
6. R12 (R13_24) customer count: De-duplicated count of unique customer IDs in the most recent 12 months (13-24 months prior to the statistical period).
7. R12 (R13_24) repurchasing customer count: De-duplicated count of unique customer IDs with transaction count ≥2 in the most recent 12 months (13-24 months prior to the statistical period).
Repurchase rate = number of repurchasing customers / total number of customers

搜集汇总

背景与挑战

背景概述

该数据集包含美妆行业客户复购相关数据，涵盖新客、老客、会员和非会员的客户数、复购客户数及复购率等指标，用于分析客户粘性和制定营销策略。数据每月更新，通过CRM系统采集加工，采用标准化算法计算复购率和环比增长。