承德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承德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模型通过计算承德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This dataset conducts user profiling for users in the Chengde City region of the Wolikuaigou platform, obtains user value analysis through algorithms, formulates marketing strategies based on the analysis results, and aims to improve user stickiness and loyalty. The RFM model, when combined with user attribute data, enables refined customer segmentation and precise marketing. Additionally, by analyzing the changing trends of users' comprehensive RFM scores, the platform can predict user lifetime value and optimize user retention strategies. The RFM model evaluates user value by calculating three dimensions for users in the Chengde City region: Recency (R), Frequency (F), and Monetary Value (M): 1. Recency (R) dimension: Calculate the number of days (D) between the user's last payment time and the analysis cutoff date (October 18, 2024), then assign scores 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. 2. Frequency (F) dimension: Based on the number of user orders in the past 180 days (C), assign scores 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. 3. Monetary Value (M) dimension: Based on the user's total consumption amount in the past 180 days (G), assign scores into 5 tiers: 5 points for G≥3000, 4 points for 2000≤G<3000, 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. Customers are then classified based on the comprehensive RFM score (X) as follows: new customers for 0≤X<1, seed customers for 1≤X<2, potential customers for 2≤X<4, important customers for 4≤X<6, and core customers for X≥6.

搜集汇总

数据集介绍

特点

该数据集包含承德市窝里快购平台533条客户消费行为数据，涵盖商品名称、订单编码、消费金额、订单数等16个字段，通过RFM模型评估用户价值并分类，用于用户画像和精准营销策略制定。数据每年更新，适用于提高用户粘性和忠诚度的场景。