Detail publikace

Understanding customer churn prediction research with structural topic models

FRIDRICH, M.

Originální název

Understanding customer churn prediction research with structural topic models

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Customer churn prediction is showing a growth in attention from both researchers and practitioners, creating a vast body of scientific works while being recognized as an indispensable tool of corporate retention activities. Thus, we aim to demonstrate the potential of structural topic models to navigate through the research articles and to identify essential themes and trends within the field of customer defection prediction. We apply a modified modeling procedure to journal articles focused on customer churn. As a result, the structural model of 38 topics is formed and examined considering topic prevalence, its changes over time, and the scientific impact (citations). We see prevailing themes tackling broad perspectives such as modeling, evaluation, and performance metrics. Furthermore, we recognize a slow decline in business & marketing aspects of churn prediction coupled with rising of more nuanced topics. At last, we discuss possible future steps in topic modeling within the domain.

Klíčová slova

Customer Churn Prediction, Natural Language Processing, Topic Modeling

Autoři

FRIDRICH, M.

Vydáno

14. 12. 2020

Nakladatel

Academy of Economic Studies in Bucharest

Místo

Bucharest, Romania

ISSN

1842-3264

Periodikum

Economic Computation and Economic Cybernetics Studies and Research

Ročník

54

Číslo

4

Stát

Rumunsko

Strany od

301

Strany do

317

Strany počet

16

URL

http://ecocyb.ase.ro/nr2020_4/19.+Martin+FRIDRICH+(T).pdf

BibTex

@article{BUT167274,
  author="Martin {Fridrich}",
  title="Understanding customer churn prediction research with structural topic models",
  journal="Economic Computation and Economic Cybernetics Studies and Research",
  year="2020",
  volume="54",
  number="4",
  pages="301--317",
  doi="10.24818/18423264/54.4.20.19",
  issn="1842-3264",
  url="http://ecocyb.ase.ro/nr2020_4/19.+Martin+FRIDRICH+(T).pdf"
}