焦作市窝里快购平台客户消费行为分析数据

通过对窝里快购平台焦作市地区的用户进行用户画像,根据算法获得用户价值分析,根据分析制定营销策略,提高用户粘性和忠诚度。RFM模型可以与用户属性数据结合,实现精细化的客户细分和精准营销。此外,通过分析用户RFM综合评分的变化趋势,平台可以预测用户生命周期价值,优化用户留存策略。RFM模型通过计算焦作市地区用户最近一次消费时间(R)、消费频率(F)和消费金额(M)这三个维度来评估用户价值。R 维度,根据时间（用户最后支付时间）距离分析时间（2024年10月18日）的天数（D）,划分为5个等级: 0≤D≤5为5分，5＜D≤10 为4分，10＜D≤20 为3分，20＜D≤30为2分，D ＞30为1分；F 维度,根据用户在过去180天订单数量（C）,划分为5个等级: 0≤C≤5为1分，5≤C≤10 为2分，10≤C≤20 为3分，20≤C≤30为4分，C≥30为5分；M 维度,根据用户在过去180天消费金额（G）,划分为5个等级，G≥3000为5分，3000≤G＜2000为4分，1000≤G＜2000为3分，500≤G＜1000为2分，0≤G＜500为1分。RFM综合评分（X）=R+F+M，再根据RFM综合评分（X）对客户进行分类，0≤X＜1为新客户，1≤X＜2为种子客户，2≤X＜4 为潜力客户，4≤X＜6为重要客户，X ≥6为核心客户

We conduct user profiling for users in the Jiaozuo City region of the Wolikuaigou platform, perform user value analysis via algorithms, and formulate marketing strategies based on the analysis to enhance user stickiness and customer loyalty. The RFM model can be combined with user attribute data to achieve refined customer segmentation and precision marketing. Additionally, by analyzing the trends of users' comprehensive RFM scores, the platform can predict customer lifetime value and optimize user retention strategies. The RFM model evaluates user value by measuring three core dimensions: Recency (R) of the user's most recent purchase in the Jiaozuo City region, purchase Frequency (F), and total consumption Monetary value (M). For the Recency (R) dimension, calculate the number of days (D) between the user's last payment timestamp and the analysis cutoff date (October 18, 2024), then categorize users into 5 tiers: 5 points for 0≤D≤5, 4 points for 5<D≤10, 3 points for 10<D≤20, 2 points for 20<D≤30, and 1 point for D>30; For the Frequency (F) dimension, based on the total number of orders (C) placed by the user over the past 180 days, categorize users into 5 tiers: 1 point for 0≤C≤5, 2 points for 5≤C≤10, 3 points for 10≤C≤20, 4 points for 20≤C≤30, and 5 points for C≥30; For the Monetary value (M) dimension, based on the total consumption amount (G) of the user over the past 180 days, categorize users into 5 tiers: 5 points for G≥3000, 4 points for 3000≤G<2000, 3 points for 1000≤G<2000, 2 points for 500≤G<1000, and 1 point for 0≤G<500. The comprehensive RFM score (X) is calculated as X = R + F + M. Subsequently, customers are classified based on their comprehensive RFM score (X): new customers for 0≤X<1, seed customers for 1≤X<2, potential customers for 2≤X<4, key customers for 4≤X<6, and core customers for X≥6.

搜集汇总

数据集介绍

特点

该数据集为焦作市窝里快购平台的客户消费行为分析数据，包含1431条记录，涵盖用户ID、商品名称、订单信息等字段。通过RFM模型对用户进行分类和价值分析，适用于用户画像构建、营销策略制定和用户生命周期价值预测。