Detection of Churned and Retained Users with Machine Learning Methods for Mobile Applications

被引：0

作者：

Gencer, Merve ^{[1
]}

Bilgin, Gokhan ^{[2
]}

Zan, Ozgur ^{[1
]}

Voyvodaoglu, Tansel ^{[1
]}

机构：

[1] Done Info & Com Syst Istanbul, Istanbul, Turkey

[2] Yildiz Tech Univ, Dept Comp Engn, Istanbul, Turkey

来源：

DESIGN, USER EXPERIENCE, AND USABILITY: USER EXPERIENCE DESIGN FOR DIVERSE INTERACTION PLATFORMS AND ENVIRONMENTS, PT II | 2014年 / 8518卷

关键词：

Machine learning; SVM; mobile applications; churned and retained users; diversity applications; classification; mobile devices; push notification; user experience; CUSTOMER ATTRITION ANALYSIS; SERVICES; MODELS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This study aims to find the different behavior patterns of churned and retained mobile application users using machine learning approach. The data for this study is gathered from the users of a mobile application (iPhone & Android). As a machine learning classifier Support Vector Machines (SVM) are used for evaluating in the detection of churned and retained users. Several features are extracted from user data to discriminate different user behaviors. Successful results are obtained and user behaviors are classified with 93% and 98% accuracy. From the diversity perspective, results of this study can be used to evaluate the differences of churned and retained users in terms of diverse user groups.

引用

页码：234 / 245

页数：12

共 12 条

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[Anonymous], 2000, Pattern Classification

[2]

AU T, 2003, J COMP INT MANAGEMEN, V6

[3]

Bishop C.M., 2006, J ELECTRON IMAGING, V16, P049901, DOI DOI 10.1117/1.2819119

[4] CRM at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription services [J].