摘要
摘要
通信技术、信息技术更新换代，智能终端硬件设备普及，成就移动互联
网蓬勃发展。在大数据时代背景下，用户的社交、消费行为向线上聚集，企业
为消费者提供产品销售、用户服务也随之从线下向线上转移，纷纷建立连接企
业产品服务与用户的新型渠道APP（移动应用程序Application，简称APP），
其意图在于记录用户数据，挖掘数据价值，为企业生产运营提供有力支持。APP
是企业实现数据驱动创新转型的重要阵地。
YN移动是Y省移动通信用户市场占有率最高的企业，用户规模超过3000万。
为应对互联网时代消费者向线上迁移的趋势，2016年建立并开始运营面向个人
用户的 YN移动 APP，旨在面向为 Y省移动用户提供通信业务办理、影音娱乐和
生活购物等综合服务内容。经过数年的运营，虽YN移动APP用户规模已经达到
千万级，但整体运营模式、运营思路还是受限于传统通信运营商业务经营管理模
式，APP用户运营管理存在问题和困难，难以适应千变万化的互联网环境。因此，
论文运用一种科学的方法解决 YN移动 APP运营管理存在的问题。首先运用 K-
means聚类算法对APP样本用户分群，其次参考AARRR模型五个方面分析提炼YN
移动APP运营管理中存在的问题，最后针对性地提出适合YN移动APP运营五个
方面的优化策略：APP获取用户优化举措；APP用户活跃度提升举措；APP用户
留存率提升举措；APP变现能力增强举措；APP用户自传播增进举措。为从事互
联网行业的产品运营经理和运营商市场分析人员提供用户运营的解决思路和解
决办法。
关键词：用户运营策略;APP;用户画像;K-means聚类算法;AARRR模型
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Abstract
Abstract
The development of internet, highlights the advantage of e-commerce marketing.
In the period of the internet technique highly prosperous, people surf in the internet,
shopping online, and making friends through network. Enterprises provide consumers
with product sales and customer service, which is also transferred from offline to online.
A lot of them have been setting up the mobile applications, aim to record user data,
mining data value, to offer powerful support for business and production. It is a new
channel connecting enterprises' products, services and users, and an important front for
realizing the transformation driven by data innovation.
YN Mobile has the highest market share of mobile communication users in Y
Province, with more than 30 million users. In response to the trend of online migration
of consumers in the Internet era, In 2016, yn mobile app for individual users was
established and started to operate, it aims to provide comprehensive services such as
communication business handling, audio-visual entertainment and life shopping for
mobile users in Y province. After several years of operation, although the user scale of
YN mobile app has reached tens of millions, however, the overall operation mode and
operation idea are still limited by the communication business operation and
management mode of traditional operators. The operation and management of APP
users is inefficient and difficult to adapt to the ever-changing Internet environment.
Therefore, this thesis demonstrates a scientific method to solve the problems existing
in the operation and management of YN mobile app. Firstly, K-means clustering
algorithm is used to cluster app sample users. Secondly, the problems existing in the
operation and management of YN mobile app are analyzed and refined according to the
five aspects of aarrr model. Finally, it puts forward the operation optimization strategy
suitable for yn mobile app. Provide solutions and solutions for product operation
managers and operators' market analysts engaged in the Internet industry.
Key words: users operation strategy; APP; user profile; K-means clustering algorithm; AARRR
model; operation strategy;
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目录
目录
摘要............................................................................................................................ I
Abstract ...................................................................................................................... II
第一章 绪论..................................................................................................................1
第一节研究背景及意义........................................................................................1
第二节国内外研究现状及评述..............................................................................2
一、国内外研究现状...............................................................................................................2
二、研究现状评述...................................................................................................................4
第三节研究思路、研究方法、技术路线、论文创新点......................................6
一、研究思路...........................................................................................................................6
二、研究方法...........................................................................................................................6
三、技术路线...........................................................................................................................7
四、论文创新点.......................................................................................................................7
第二章 概念介绍与理论基础......................................................................................8
第一节用户画像......................................................................................................8
一、用户画像概念与界定.......................................................................................................8
二、用户画像模型与方法.......................................................................................................9
第二节数据挖掘及聚类算法................................................................................10
一、数据挖掘概念及方法.....................................................................................................10
二、K-means聚类算法介绍..................................................................................................11
第三节 AARRR模型.................................................................................................12
一、获取用户(Acquisition)...............................................................................................14
二、提高活跃度 (Activation)...........................................................................................15
三、提高留存率(Retention)...............................................................................................16
四、获取收入 (Revenue).....................................................................................................16
五、自传播(Refer)...............................................................................................................17
第三章 YN移动 APP运营现状介绍........................................................................19
第一节 YN移动APP发展情况介绍.......................................................................19
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