儿童洗牙服务线上退单率分析数据

每月统计退单数和总订单数，结合前三个月的数据，计算历史退单率均值和标准差，并以Z-Score方法判定当月儿童洗牙服务线上退单率是否超出正常波动范围。当|Z|＞2时，即识别出异常高或低的退单波动，提示口腔门诊及时排查原因，如服务变动、机构问题或活动影响。通过退单率分析预警退单率异常，帮助其精准锁定风险环节，优化服务流程。该数据亦可为行业内其他口腔医疗机构提供风险监控的参考。1.数据采集和预处理：（1）从公司口腔连锁门诊管理系统采集儿童洗牙服务有关的销售数据，字段包括：线上平台名称、服务名称、服务套餐名称（共有2类套餐）、门店编号（公司拥有7家门店）、分析月份T、当月退单数、当月订单数、T-1月退单数、T-2月退单数、T-3月退单数、T-1月订单数、T-2月订单数、T-3月订单数；（2）对采集的数据进行清洗；2.计算当月退单率、T-1月退单率、T-2月退单率、T-3月退单率：退单率 = 某月退单数 / 当月订单数；计算历史退单率均值：历史退单率均值 = （T-1月退单数 + T-2月退单数 + T-3月退单数）/ 3；3.通过Z-Score方法识别异常：历史退单率标准差 = √{[(T-1月退单率-历史退单率均值)^2+(T-2月退单率-历史退单率均值)^2+(T-3月退单率-历史退单率均值)^2]/3}；当月Z-Score = (当月退单率 – 历史退单率均值)/历史退单率标准差；4.异常判定：若|Z|＞2,说明当月退单率异常；若|Z|≤2，说明当月退单率正常。This dataset is designed to monthly track the number of canceled orders and total orders for pediatric teeth cleaning services, combine data from the prior three months to calculate the mean and standard deviation of historical cancellation rates, and use the Z-Score method to determine whether the online cancellation rate of the current month falls outside the normal fluctuation range. When |Z| > 2, abnormally high or low cancellation rate fluctuations are identified, prompting dental clinics to timely investigate potential causes such as service changes, institutional issues, or promotional campaign impacts. This cancellation rate analysis aims to alert abnormal cancellation rates, help clinics accurately identify risk-prone links, and optimize service processes. Additionally, the dataset can serve as a reference for risk monitoring for other dental medical institutions in the industry. 1. Data Collection and Preprocessing: (1) Collect sales data related to pediatric teeth cleaning services from the company’s dental chain clinic management system. The collected fields include: online platform name, service name, service package name (total of 2 types of packages), store ID (the company operates 7 stores), analysis month T, number of canceled orders in month T, total orders in month T, number of canceled orders in month T-1, number of canceled orders in month T-2, number of canceled orders in month T-3, total orders in month T-1, total orders in month T-2, and total orders in month T-3. (2) Clean the collected data. 2. Calculate Cancellation Rates: Calculate the cancellation rate for each month using the formula: Cancellation Rate = (Number of Canceled Orders in a Month) / (Total Orders in that Month). Thus, the current month’s cancellation rate, T-1 month’s cancellation rate, T-2 month’s cancellation rate, and T-3 month’s cancellation rate are obtained. Calculate the historical average cancellation rate: Historical Average Cancellation Rate = (Number of Canceled Orders in T-1 + Number of Canceled Orders in T-2 + Number of Canceled Orders in T-3) / 3. 3. Identify Abnormalities via Z-Score Method: Calculate the historical standard deviation of cancellation rates using the formula: Historical Cancellation Rate Standard Deviation = √{[(T-1 Cancellation Rate - Historical Average Cancellation Rate)² + (T-2 Cancellation Rate - Historical Average Cancellation Rate)² + (T-3 Cancellation Rate - Historical Average Cancellation Rate)²] / 3} Then calculate the current month’s Z-Score: Current Month Z-Score = (Current Month Cancellation Rate - Historical Average Cancellation Rate) / Historical Cancellation Rate Standard Deviation 4. Abnormality Judgment: If |Z| > 2, the cancellation rate of the current month is deemed abnormal; if |Z| ≤ 2, the cancellation rate of the current month is deemed normal.

搜集汇总

背景与挑战

背景概述

该数据集包含儿童洗牙服务的线上订单和退单数据，规模为642条，每月更新，用于计算退单率并通过Z-Score方法识别异常波动，以帮助口腔门诊及时排查原因和优化服务流程。数据源自企业自行产生，涵盖多个线上平台和门店的详细统计信息。