合肥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。对采集到的合肥市数据进行清洗、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 model computes the RFE score based on three metrics: Recency (R, time since a user's last visit), Frequency (F, total visit frequency), and Engagements (E, page interaction level). It is designed to assess user activeness, classify users into multiple activeness tiers, and deliver targeted marketing initiatives (e.g., event invitations, precise ad placement, member activity recommendations) based on these tiers to enhance user engagement. The RFE model offers data support for all enterprises that require activeness analysis and management of their members or users.

1. Data Collection and Preprocessing: Data was collected from the Fangtai Happiness Home App. The collected datasets from Hefei City were cleaned, denoised, desensitized, aggregated and analyzed to derive the values of R (time since last visit), F (visit frequency), and E (page interaction level).

2. Customer Profiling and Score Calculation:
(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 = 0.3 × R_score + 0.3 × F_score + 0.4 × E_score;

3. Data Application:
Customers are tiered based on their RFE scores as follows:
- Tier E: RFE Score ≤ 1;
- Tier D: 1 < RFE Score ≤ 2;
- Tier C: 2 < RFE Score ≤ 3;
- Tier B: 3 < RFE Score ≤ 4;
- Tier A: RFE Score > 4;
Subsequently, user activeness analysis is conducted per their tier. For instance, for users in Tiers C, D and E with favorable interaction data during each visit, targeted measures including event invitations, precise ad placement, and member activity recommendations will be implemented to increase their revisit frequency.

搜集汇总

数据集介绍

特点

合肥市用户活跃度分级数据是一个包含859条记录的数据集，每日更新，适用于制造业。该数据集通过RFE模型对用户活跃度进行分级，支持企业进行精准营销和用户活跃度管理。