黄龙旅行家锦鲤卡会员分析数据

根据会员运营管理需求，通过对锦鲤卡会员的2024年消费行为进行用户画像和标签运算将会员数据分组分群，借助RFM模型开展用户价值分析，针对不同级别客户通过多种营销手段有针对性的制定广告营销策略，盘活不活跃用户，引导活跃用户续费，提高用户粘性和忠诚度，提升会员收入。RFM模型还可以与其他用户属性数据相结合，比如线上或线下发卡渠道、会籍到期时间等，实现精细化的客户细分和精准营销。（1）数据来源：采集黄龙旅行家锦鲤卡会员的基础消费数据，对数据进行清洗、去除无效数据等操作。 （2）数据处理：采用RFM数据模型。通过对会员信息的聚类汇总消费频次F、消费总金额M、最近一次消费发生或会员注册距离会籍到期时间的间隔R，以此为维度对客户进行分类。 （3）数据计算：F值得分=消费频次F/当年最高消费频次*10，当年最高消费频次为该年度内锦鲤卡会员消费频次的最高值；M值得分=消费金额M/当年最高消费总金额*10，当年最高消费总金额为该年度锦鲤卡会员下单金额的最高值；R值得分=（365-距离到期天数R）/36，距离到期天数R为锦鲤卡会员最近一次消费发生或成为会员距离会籍到期时间的间隔；RFM综合得分=a*F值得分+b*M值得分+c*R值得分，a，b，c为权重系数，分别是0.35,0.3,0.35。再根据RFM综合得分对客户进行分类，RFM综合得分大于等于4为忠诚客户，RFM综合得分小于1分为待流失客户。Based on the requirements of member operation and management, we conduct user profiling and tag calculation on the 2024 consumption behavior of Koi Card members to group and segment member data, carry out user value analysis with the RFM model, formulate targeted advertising and marketing strategies for different-level customers through various marketing means, revitalize inactive users, encourage active users to renew their memberships, enhance user stickiness and loyalty, and increase member revenue. The RFM model can also be combined with other user attribute data, such as online or offline card issuance channels and membership expiration dates, to achieve refined customer segmentation and precision marketing. (1) Data Source: Basic consumption data of Huanglong Traveler Koi Card members is collected, followed by data cleaning, invalid data removal and other preprocessing operations. (2) Data Processing: The RFM data model is adopted. Customers are classified using three dimensions derived from clustered member information: consumption frequency (F), total consumption amount (M), and the interval (R) between the member's last consumption or membership registration and the membership expiration date. (3) Data Calculation: F score = (Consumption Frequency F / Annual Maximum Consumption Frequency) × 10, where the annual maximum consumption frequency refers to the highest consumption frequency among all Koi Card members in the current year; M score = (Total Consumption Amount M / Annual Maximum Total Consumption Amount) × 10, where the annual maximum total consumption amount refers to the highest order amount of Koi Card members in the current year; R score = (365 - Days to Expiry R) / 36, where Days to Expiry R is the interval between the member's last consumption or membership enrollment and the membership expiration date. The comprehensive RFM score = a*F score + b*M score + c*R score, where a, b and c are weight coefficients set to 0.35, 0.3 and 0.35 respectively. Customers are then categorized based on their comprehensive RFM scores: those with a score ≥ 4 are classified as loyal customers, while those with a score < 1 are classified as pending churn customers.