重庆市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。对采集到的重庆市数据进行清洗、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 scoring model calculates user activity scores based on three metrics: Recency (R, time since the user's last visit), Frequency (F, visit count), and Engagements (E, page interaction level). It is used to evaluate user activity, classify users into multiple activity tiers, and carry out differentiated marketing activities tailored to each tier—such as event invitations, targeted advertising, and member activity recommendations—to enhance user activity. The RFE model can provide data support for all enterprises that require activity analysis and management of their members or users.
1. Data Collection: Data was collected from the FOTILE Happy Home App. After cleaning, denoising, desensitization, aggregation and analysis of the collected data from Chongqing, the values of R (Recency of last visit), F (Visit Frequency) and E (Page Engagement) were obtained.
2. Customer Profile Construction:
(1) Scoring Rules:
- 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 = 0.3 × R Score + 0.3 × F Score + 0.4 × E Score.
3. Data Application:
Customers are classified based on their RFE scores: Grade E if RFE Score ≤ 1; Grade D if 1 < RFE Score ≤ 2; Grade C if 2 < RFE Score ≤ 3; Grade B if 3 < RFE Score ≤ 4; Grade A if RFE Score > 4. Then analyze user activity based on their customer grades. For example, for users with Grade C, D or E but good interaction data during each visit, focus on improving their revisit frequency through measures such as event invitations, targeted advertising, and member activity recommendations.

搜集汇总

数据集介绍

特点

该数据集包含重庆市用户的活跃度分级信息，通过RFE模型（基于最近访问时间、访问频率和页面互动度）计算用户活跃度得分，并将用户分为A到E五个等级。数据每日更新，适用于需要分析和管理用户活跃度的企业，支持精准营销活动。