scholarly journals Telco churn analysis classification using a wavelet and RBF approach

2006 ◽  
Author(s):  
Â. M. Cister ◽  
N. F. F. Ebecken
Keyword(s):  
Churn Analysis

Guided Exploration

2021 ◽  
Vol 5 (EICS) ◽  
pp. 1-34
Author(s):  
Markus Weninger ◽  
Elias Gander ◽  
Hanspeter Mössenböck
Keyword(s):  
Time Behavior ◽  
Monitoring Tool ◽  
Memory Leak ◽  
Root Cause ◽  
Churn Analysis ◽  
Monitoring Tools ◽  
Guided Exploration ◽  
Monitoring Applications ◽  
Novice Users ◽  
Memory Monitoring

Many monitoring tools that help developers in analyzing the run-time behavior of their applications share a common shortcoming: they require their users to have a fair amount of experience in monitoring applications to understand the used terminology and the available analysis features. Consequently, novice users who lack this knowledge often struggle to use these tools efficiently. In this paper, we introduce the guided exploration (GE) method that aims to make interactive monitoring tools easier to use and learn. In general, tools that implement GE should provide four support operations on each analysis step: they should automatically (1) detect and (2) highlight the most important information on the screen, (3) explain why it is important, and (4) suggest which next steps are appropriate. This way, tools guide users through their analysis processes, helping them to explore the root cause of a problem. At the same time, users learn the capabilities of the tool and how to use them efficiently. We show how GE can be implemented in new monitoring tools as well as how it can be integrated into existing ones. To demonstrate GE's feasibility and usefulness, we present how we extended the memory monitoring tool AntTracks to provided guided exploration support during memory leak analysis and memory churn analysis. We use these guidances in two user scenarios to inspect and improve the memory behavior of the monitored applications. We hope that our contribution will help usability researchers and developers in making monitoring tools more novice-friendly by improving their usability and learnability.

scholarly journals A Hybrid Two-Level Support Vector Machine-Based Method for Churn Analysis

2021 ◽  
Author(s):  
Ferdi Sarac ◽  
Huseyin Seker ◽  
Marcin Lisowski ◽  
Alan Timothy
Keyword(s):  
Support Vector Machine ◽  
Support Vector ◽  
Churn Analysis

Churn analysis: Predicting churners

2014 ◽  
Author(s):  
Navid Forhad ◽  
Md. Shahriar Hussain ◽  
Rashedur M Rahman
Keyword(s):  
Churn Analysis

scholarly journals A Survey on Churn Analysis in Various Business Domains

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 220816-220839
Author(s):  
Jaehyun Ahn ◽  
Junsik Hwang ◽  
Doyoung Kim ◽  
Hyukgeun Choi ◽  
Shinjin Kang
Keyword(s):  
Churn Analysis

Churn Analysis of Maximum Level Users in Online Games

2017 ◽  
Vol 44 (3) ◽  
pp. 314-322 ◽  
Author(s):  
Kunwoo Park ◽  
Meeyoung Cha
Keyword(s):  
Maximum Level ◽  
Online Games ◽  
Churn Analysis

Social Network Analysis (SNA) for Churn Mitigation/Detection

2014 ◽  
pp. 63-141
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Customer Relationship ◽  
Full Potential ◽  
Complex Environments ◽  
Churn Analysis ◽  
Advanced Analytics ◽  
Churn Management

Social network analysis is intentionally covered in a separate chapter for two reasons. First, the importance of this method has rapidly increased in past few years, and second, there are very few useable studies that cover social network analysis concepts in churn management. By understanding the methods explained in Chapter 3 and combining them with knowledge of SNA concepts, the analysts (readers) can unlock the full potential of advanced analytics in one of the most important fields of research today, customer relationship and especially churn analysis. With the ability to understand how those metrics can be used, integration of those methods into more complex environments is explained regarding the key topic, churn management.

Setting (Realistic) Business Aims

2014 ◽  
pp. 26-40
Keyword(s):  
Early Warning ◽  
Early Warning Systems ◽  
Full Potential ◽  
Warning Systems ◽  
Conceptual Level ◽  
Churn Analysis ◽  
Key Points ◽  
Methods And Techniques

This chapter explains different perspective of churn analysis and points out the importance of understanding what really can or cannot be done. In addition, it is important to understand common errors analysts (readers) have, so that one can be aware of them when planning and conducting churn analyses. It is advisable for the reader to move back to the introduction and Chapter 1 after finishing reading in order to once again understand the full potential and restrictions of the proposed methods and techniques. Although this chapter covers churn topics on a conceptual level, it is very important for the reader to be able to understand and express key points on this level. By using industry-related cases and by combining churn with early warning systems, the complete scope is covered, and the reader can move to the next level, techniques, explained in next chapter.

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