BUSINESS INFORM JOURNAL.

УКР

ENG

Search:

REGISTRATION CERTIFICATE

KV #19905-9705 PR dated 02.04.2013.

FOUNDERS

RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE)

According to the decision No. 802 of the National Council of Television and Radio Broadcasting of Ukraine dated 14.03.2024, is registered as a subject in the field of print media.
ID R30-03156

PUBLISHER

Liburkina L. M.

SITE SECTIONS

Optimization of the Management of the Customer Base of a Telecommunications Company Using Artificial Intelligence Methods
Yurchenko V. V., Telnova H. V.

Yurchenko, Viktoriia V., and Telnova, Hanna V. (2024) “Optimization of the Management of the Customer Base of a Telecommunications Company Using Artificial Intelligence Methods.” Business Inform 9:101–107.
https://doi.org/10.32983/2222-4459-2024-9-101-107

Section: Information Technologies in the Economy

Article is written in Ukrainian
Downloads/views: 1

Download article (pdf) -

UDC 339.1:330.4:004.04

Abstract:
The aim of the study is to substantiate the use of machine learning and statistical analysis methods, in particular the CHAID (Chi-squared Automatic Interaction Detection) algorithm, to identify key factors influencing customer churn and telecommunications company revenue. The research is directed towards developing effective strategies for managing the customer base and optimizing business processes in the telecommunications industry. The article conducts a comprehensive analysis of the client base of a telecommunications company using the method of decision trees. The six most important factors that have the greatest influence on customers’ decisions to continue or terminate the use of services have been identified: type of contract, type of Internet service, duration of use of services, use of movie streaming services, method of payment and retiree status. The study found that these factors affect not only customer churn but also the company’s revenue from each customer. This highlights the importance of a comprehensive approach to analyzing the customer base, which takes into account both churn risks and the financial aspects of customer interactions. Based on the results obtained, the introduction of an individual approach to clients with different characteristics has been proposed. Such a strategy will allow you to more effectively meet the needs of different segments of the customer base, increase their loyalty and maximize the company’s revenue. The study opens up prospects for further research in the direction of optimizing customer base management, in particular in the development of methods for interpreting machine learning models, improving methods for segmenting the customer base, and developing dynamic models that take into account changes in customer behavior over time.

Keywords: artificial intelligence, customer base management, telecommunications, customer segmentation, churn forecasting, machine learning, data analysis, CHAID algorithm, decision trees, business process optimization, customer loyalty, service personalization, statistical analysis, model interpretation, dynamic segmentation models.

Tabl.: 2. Bibl.: 9.

Yurchenko Viktoriia V. – Masters Student, State University «Kyiv Aviation Institute» (1 Lubomyra Husara Ave., Kyiv, 03680, Ukraine)
Email: [email protected]
Telnova Hanna V. – Doctor of Sciences (Economics), Associate Professor, Professor, Department of Business Analytics and Digital Economy, State University «Kyiv Aviation Institute» (1 Lubomyra Husara Ave., Kyiv, 03680, Ukraine)
Email: [email protected]

List of references in article

Pang, G. et al. “Deep Learning for Anomaly Detection: A Review“ю ACM Computing Surveys, art. 38, vol. 54, no. 2 (2021). DOI: https://doi.org/10.1145/343995
Koller, D., and Friedman, N. Probabilistic Graphical Models: Principles and Techniques. MIT Press, 2009.
Lundberg, S. M., and Lee, S.-I. “A Unified Approach to Interpreting Model Predictions“. Advances in Neural Information Processing Systems, vol. 30 (2017): 4765-4774. DOI: https://doi.org/10.48550/arXiv.1705.07874
Vasylenko, A. M., and Hlybovets, A. M. “Systema upravlinnia kliientskoiu bazoiu modeli SaaS na prykladi kompanii strakhovoho brokera“ [Customer Relationship Management System as a SaaS on Example of Insurance Broker Company]. Naukovi zapysky NaUKMA. Seriia «Kompiuterni nauky», vol. 3 (2020): 31-35. DOI: https://doi.org/10.18523/2617-3808.2020.3.31-35
Harkavenko, V. O., and Stets, O. V. “Ekonomiko-matematychna model upravlinnia kliientskoiu bazoiu pidpryiemstva“ [Economic and Mathematical Model of Enterprise Client Base Management]. Stratehiia ekonomichnoho rozvytku Ukrainy, no. 50 (2022): 177-196. DOI: https://doi.org/10.33111/sedu.2022.50.177.196
Kataiev, A. V. “Tsinnist kliientskoi bazy yak bazys pryiniattia marketynhovykh rishen: evoliutsiia modelei otsinky“ [The Value of the Customer Base as a Basis for Making Marketing Decisions: Evolution of Valuation Models]. Efektyvna ekonomika, no. 5 (2023). DOI: http://doi.org/10.32702/2307-2105.2023.5.48
Rats, O. M. “Zabezpechennia loialnosti kliientiv yak skladnyk mekhanizmu upravlinnia kliientskoiu bazoiu banku“ [Providing the Loyality of Clients as the Composition of the Mechanism of Management of the Client Base of the Bank]. Naukovyi visnyk Khersonskoho derzhavnoho universytetu. Seriia «Ekonomichni nauky». 2018. https://ej.journal.kspu.edu/index.php/ej/article/view/216/211
Roskladka, N. O., Roskladka, A. A., and Dzyhman, O. O. “Klasternyi analiz kliientskoi bazy danykh pidpryiemstv sfery posluh“ [Cluster Analysis of Customer Database of the Service Enterprises]. Tsentralnoukrainskyi naukovyi visnyk. Seriia «Ekonomichni nauky», no. 2 (2019): 151-159. DOI: https://doi.org/10.32515/2663-1636.2019.2(35).151-159
“IBM Sample Data Sets. Telco Customer Churn“. Kaggle. https://www.kaggle.com/datasets/blastchar/telco-customer-churn

FOR AUTHORS

License Contract

Conditions of Publication

Article Requirements

Regulations on Peer-Reviewing

Publication Contract

Current Issue

Frequently asked questions

INFORMATION

The Plan of Scientific Conferences

OUR PARTNERS

Journal «The Problems of Economy»

The site and its metadata are licensed under CC BY-SA.

Write to webmaster