河南省品牌营销活动用户活跃指数分析数据

研究河南省内，品牌在店铺投放各类营销活动时，已注册的门店用户的参与情况（一个门店主体即为一个用户）。包括合作品牌数量，参与活动类型，通过ST模型，计算活跃指数。基于这一部分数据，品牌可以了解门店营销状况以及未来可能的变化趋势，有助于指导品牌营销模式的优化和迭代，有助于在投入产出规划上提供帮助，为对店商活跃度与品牌营销策略分析等场景有需求的企业、机构提供数据支持，同时辅助当地政府进行市场监管。1.数据采集：数据采集来自惠合科技合法自有的e店佳等店商平台（平台致力于在品牌-商户-消费者之间构建业务服务桥梁）。研究2024年河南省内，品牌在店铺投放各类营销活动时，已注册的门店用户的参与情况，包括合作品牌数量（SUM）简称为S，参与活动类型（TYPE）简称为T。进行分析加工，对数据进行清洗、去重，剔除无效数据。；2.构建用户/门店画像：（1）打分：河南省内已注册的门店，每参与一个品牌的营销活动， SUM得分记1，累加计算；每参与一种活动，TYPE得分记1，累计计算；（2）计算ST得分：ST得分=S得分*0.3+T得分*0.4（0.3和0.4为加权计算系数）； 3、数据应用： 根据ST得分对河南省门店用户活跃度进行分级：0≤ST得分≤0.7，为D级活跃度；0.7<ST得分≤1.0，为C级活跃度；1.0<ST得分≤1.4，为B级活跃度；1.4<ST得分，为A级活跃度。对用户的活跃度做分析，如门店活跃度等级为D、C，针对这部分用户通过活动邀请提升参与活动的意愿;如门店活跃度等级为B，通过优惠方案提高活跃度；如门店活跃度等级为A，针对这部分用户通过重点活动邀请、专享优惠投放等稳定活动活跃度。

This study investigates the participation status of registered store users (each store entity is counted as one user) when brands launch various marketing campaigns on stores within Henan Province. The study covers two core indicators: the count of partnering brands and the types of participated marketing activities, and calculates the user activity index via the ST Model. Based on this dataset, brands can obtain insights into the current marketing performance of stores and potential future trends, which supports the optimization and iteration of brand marketing models, aids in input-output planning, provides data support for enterprises and institutions in need of scenarios such as store merchant activity analysis and brand marketing strategy analysis, and also assists local governments in market supervision.

1. Data Collection
Data is collected from legally owned e-Dianjia and other store merchant platforms under Huige Technology, which is committed to building a business service bridge between brands, merchants and consumers. This study focuses on the participation status of registered store users when brands launch various marketing campaigns on stores in Henan Province in 2024, including the count of partnering brands (abbreviated as S, originally denoted by SUM) and the types of participated marketing activities (abbreviated as T, originally denoted by TYPE). Subsequently, data analysis and processing are conducted, including data cleaning, deduplication and removal of invalid data.

2. Construction of User/Store Portraits
(1) Scoring: For each registered store in Henan Province, 1 point is added to the S score (corresponding to the count of partnering brands) for each marketing campaign of a brand that the store participates in, with the total calculated via cumulative summation; 1 point is added to the T score (corresponding to the types of participated marketing activities) for each distinct type of campaign that the store participates in, with the total calculated via cumulative accumulation.
(2) ST Score Calculation: The ST score is calculated as: ST Score = 0.3 * S_score + 0.4 * T_score, where 0.3 and 0.4 are the weighted coefficients.

3. Data Application
Classify the activity levels of store users in Henan Province based on their ST scores:
- Level D: 0 ≤ ST score ≤ 0.7
- Level C: 0.7 < ST score ≤ 1.0
- Level B: 1.0 < ST score ≤ 1.4
- Level A: ST score > 1.4
Analyze user activity levels: For stores with activity levels D or C, send campaign invitations to increase their willingness to participate in activities; for stores with Level B, provide preferential schemes to improve their activity levels; for stores with Level A, use targeted campaign invitations and exclusive preferential offers to stabilize their activity levels.

搜集汇总

数据集介绍

特点

该数据集包含501条记录，记录了河南省内品牌营销活动中门店用户的参与情况，包括合作品牌数量、参与活动类型和活跃度评分。数据每年更新，适用于品牌营销策略优化和政府市场监管。