连云港市地区口腔门诊用户分级分析数据

为更好地了解连云港市区域用户在口腔科健康服务中的价值分层与行为特征，我单位对相关医疗服务数据进行采集并开展医疗RFM分析。本数据集旨在通过R（消费间隔天数）、F（消费频率）、M（消费总金额）三个核心维度，剖析不同用户群体对医疗服务的依赖程度、消费能力及近期活跃度，评估用户在医疗服务选择中的稳定性与潜在价值，以及确定针对性的服务优化与客户维系方案。​通过深入解读医疗RFM指标所反映的用户行为规律，医疗服务提供者能够精准识别高价值用户、潜力用户及需重点挽留用户，从而优化资源配置，为不同层级用户提供适配的服务内容与沟通策略，在提升用户满意度的同时，实现医疗资源的高效利用。同时，这些基于RFM分析的用户分层数据，也能为政府或行业组织制定医疗服务规划、医保政策调整及区域医疗资源布局等提供扎实的数据支撑，推动医疗服务体系更贴合民众实际需求。本次数据采集连云港市地区针对2024年内的口腔医疗服务用户行为数据，旨在通过用户消费行为分析实现RFM用户价值分层。一、消费间隔天数=分析时间-最近一次消费时间，R（消费间隔天数）评分：5分为消费间隔天数≤30天（近1个月内消费）、4分为消费间隔天数31-90天（1-3个月内消费）、3分为消费间隔天数91-180天（3-6个月内消费）、2分为消费间隔天数181-365天（6个月-1年消费）、1分为消费间隔天数>365 天（1年以上未消费）；二、F（消费频率）评分：5分为消费次数≥10次、4分为消费次数7-9次、3分为消费次数4-6次、2分为消费次数2-3次、1分为消费次数1次；三、M（消费总金额）评分：5分为消费总金额>3000元、4分为消费总金额1001-3000元、3分为消费总金额501-1000元、2分为消费总金额101-500元、1分为消费总金额≤100元；四、RFM评分= R评分×40% + F 评分×30% + M评分×30%；五、用户分级规则（基于RFM评分）：A级（核心价值用户）为RFM评分4.1-5分，特征：最近消费、高频、高额消费，需重点维护、B级（高潜力用户）为RFM评分3.1-4分，特征：消费较近、中高频、中高消费、C级（一般价值用户）为RFM评分2.1-3分，特征：消费间隔中等、中低频、中等消费、D级（低价值 / 流失用户）为RFM评分1-2分，特征：久未消费、低频、低消费，需激活或放弃。

To better understand the value stratification and behavioral characteristics of regional users in Lianyungang City regarding oral health services, our organization collected relevant medical service data and conducted medical Recency-Frequency-Monetary (RFM) analysis. This dataset aims to analyze the dependence, consumption capacity and recent activity of different user groups on medical services, evaluate the stability and potential value of users in their choice of medical services, and determine targeted service optimization and customer retention strategies, through three core dimensions: Recency (R: Days since last consumption), Frequency (F: Number of consumption occasions) and Monetary (M: Total consumption amount).

By deeply interpreting the user behavior rules reflected by medical RFM indicators, medical service providers can accurately identify high-value users, potential users and users requiring key retention, so as to optimize resource allocation, provide tailored service contents and communication strategies for users at different levels, improve user satisfaction while achieving efficient utilization of medical resources. Meanwhile, these user stratification data based on RFM analysis can also provide solid data support for governments or industry organizations to formulate medical service plans, adjust medical insurance policies and layout regional medical resources, promoting the medical service system to better fit the actual needs of the public.

This dataset collects user behavior data of oral medical services in Lianyungang City during 2024, aiming to realize RFM-based user value stratification through the analysis of user consumption behaviors.

1. Recency (R) scoring rules: 5 points for days since last consumption ≤30 (consumed within the last month); 4 points for 31-90 days (consumed 1 to 3 months ago); 3 points for 91-180 days (consumed 3 to 6 months ago); 2 points for 181-365 days (consumed 6 months to 1 year ago); 1 point for >365 days (no consumption for over 1 year).
2. Frequency (F) scoring rules: 5 points for ≥10 consumption times; 4 points for 7-9 times; 3 points for 4-6 times; 2 points for 2-3 times; 1 point for 1 consumption.
3. Monetary (M) scoring rules: 5 points for total consumption amount >3000 yuan; 4 points for 1001-3000 yuan; 3 points for 501-1000 yuan; 2 points for 101-500 yuan; 1 point for total consumption amount ≤100 yuan.
4. Overall RFM score calculation formula: RFM score = 40% × R score + 30% × F score + 30% × M score.
5. User classification rules (based on overall RFM score):
- Level A (Core High-Value Users): 4.1-5 points, characterized by recent consumption, high-frequency and high-spending behavior, requiring key maintenance;
- Level B (High-Potential Users): 3.1-4 points, characterized by relatively recent consumption, medium-to-high frequency and medium-to-high spending;
- Level C (General Value Users): 2.1-3 points, characterized by medium consumption interval, medium-to-low frequency and medium spending;
- Level D (Low-Value / Churned Users): 1-2 points, characterized by long time since last consumption, low-frequency and low spending, requiring activation or being abandoned.

搜集汇总

背景与挑战

背景概述

该数据集聚焦连云港市口腔门诊用户，包含748条记录，采用RFM模型（消费间隔天数、频率和总金额）对用户进行分级，从A级（核心价值用户）到D级（低价值/流失用户），旨在分析用户消费行为特征，帮助优化医疗服务和资源分配，每年更新一次。