山东省用户活跃度分级数据

RFE模型是根据用户最近一次访问时间R（ Recency）、访问频率 F（Frequency）和页面互动度 E（Engagements）计算得出的RFE得分。 评估用户的活跃度，将活跃度分为多个等级，以根据不同的活跃等级开展不同的营销活动。例如通过活动邀请、 精准广告投放、会员活动推荐等提升用户的活跃度。RFE模型可以为所有需要对会员或用户进行活跃度分析管理的企业提供数据支持。1、 数据采集自方太幸福家App。对采集到的山东省数据进行清洗、降噪、脱敏、聚集、分析，得到R（最近访问时间）、F（访问频次）、E（页面互动度）的值；
2、构建顾客画像：
（1）打分：
-R得分：R<31，得5分；30<R<91，得4分；90<R<181，得3分；180<R<241，得2分；R>240，得1分；
-F得分：F<11，得1分；10<F<16，得2分；15<F<21，得3分；20<F<26，得4分；F>25，得5分；
-E得分：E<4，得1分；3<E<9，得2分；8<E<16，得3分；15<E<21，得4分；E>20，得5分；
（2）计算RFE得分：RFE得分=R得分*0.3+F得分*0.3+E得分*0.4；
3、数据应用：
根据RFE得分对顾客进行分级：RFE得分≤1，为E级；1<RFE得分≤2，为D级；2<RFE得分≤3，为C级；3<RFE得分≤4，为B级；RFE得分>4，为A级；进而根据客户等级，对用户的活跃度做分析，如顾客等级为C、D、E，但每次访问时的交互数据良好，则针对这部分用户重点通过活动邀请、精准广告投放、会员活动推荐等提升用户回访频率。

The RFE Model is a scoring framework calculated using three metrics: Recency (R, the user’s most recent access timestamp), Frequency (F, the user’s total access times), and Engagements (E, the user’s page interaction level). It is employed to assess user activity, categorize users into multiple activity tiers, and implement targeted marketing strategies based on different tiers—such as event invitations, precision advertising, and member activity recommendations—to boost user activity. The RFE Model can offer data support for all enterprises requiring activity analysis and management of their members or users.
1. Data was collected from the Fotile Happy Home App. The data from Shandong Province underwent cleaning, denoising, desensitization, aggregation and analysis to derive the values of R (most recent access time), F (access frequency) and E (page interaction level);
2. Customer profiling construction:
(1) Scoring criteria:
- R score: 5 points if R < 31; 4 points if 30 < R < 91; 3 points if 90 < R < 181; 2 points if 180 < R < 241; 1 point if R > 240;
- F score: 1 point if F < 11; 2 points if 10 < F < 16; 3 points if 15 < F < 21; 4 points if 20 < F < 26; 5 points if F > 25;
- E score: 1 point if E < 4; 2 points if 3 < E < 9; 3 points if 8 < E < 16; 4 points if 15 < E < 21; 5 points if E > 20;
(2) RFE score calculation: RFE score = R score × 0.3 + F score × 0.3 + E score × 0.4;
3. Data application:
Customers are classified based on their RFE scores: Grade E for RFE score ≤ 1; Grade D for 1 < RFE score ≤ 2; Grade C for 2 < RFE score ≤ 3; Grade B for 3 < RFE score ≤ 4; Grade A for RFE score > 4. Further analysis of user activity is conducted based on customer tiers: for users belonging to Grade C, D or E but with good interaction data per visit, focus on enhancing their revisit frequency via measures including event invitations, precision advertising and member activity recommendations.

搜集汇总

数据集介绍

特点

山东省用户活跃度分级数据集包含1893条数据，每日更新，基于RFE模型（最近访问时间、访问频率、页面互动度）对用户活跃度进行分级，适用于精准营销和用户活跃度分析。