Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach

Özge H. Namlı; Seda Yanık; Faranak Nouri; N. Serap Şengör; Yusuf Mertkan Koyuncu; İrem Küçükali

doi:10.1007/978-3-030-51156-2_109

Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach

Özge H. Namlı, Seda Yanık^*, Faranak Nouri, N. Serap Şengör, Yusuf Mertkan Koyuncu, İrem Küçükali

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Today one of the challenges of companies is to decrease call center costs while improving the customer experience. In this study, we make prediction and proactively take action in order to solve customer problems before they reach the customer call center. We use machine learning techniques and train models with a dataset of an internet service provider’s several different systems. We first use supervised techniques to classify the customers having slow internet connection problems and normal internet connection. We apply two classification approaches, multi perceptron neural networks and radial basis neural networks. Then, we cluster the same dataset using unsupervised techniques, namely Kohonnen’s neural networks and Adaptive Resonance Theory neural networks. We evaluate the classification and clustering results using measures such as recall, accuracy and Davies-Bouldin index, respectively.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques
Subtitle of host publication	Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Publisher	Springer
Pages	941-948
Number of pages	8
ISBN (Print)	9783030511555
DOIs	https://doi.org/10.1007/978-3-030-51156-2_109
Publication status	Published - 2021
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey Duration: 21 Jul 2020 → 23 Jul 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1197 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2020
Country/Territory	Turkey
City	Istanbul
Period	21/07/20 → 23/07/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Artificial neural networks
Call center problem prediction
Classification
Clustering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-51156-2_109

Cite this

Namlı, Ö. H., Yanık, S., Nouri, F., Şengör, N. S., Koyuncu, Y. M., & Küçükali, İ. (2021). Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference (pp. 941-948). (Advances in Intelligent Systems and Computing; Vol. 1197 AISC). Springer. https://doi.org/10.1007/978-3-030-51156-2_109

Namlı, Özge H. ; Yanık, Seda ; Nouri, Faranak et al. / Improving Customer Experience for an Internet Service Provider : A Neural Networks Approach. Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A. Cagri Tolga. Springer, 2021. pp. 941-948 (Advances in Intelligent Systems and Computing).

@inproceedings{b51ed6e88ba24dfab7db91a722ebe323,

title = "Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach",

abstract = "Today one of the challenges of companies is to decrease call center costs while improving the customer experience. In this study, we make prediction and proactively take action in order to solve customer problems before they reach the customer call center. We use machine learning techniques and train models with a dataset of an internet service provider{\textquoteright}s several different systems. We first use supervised techniques to classify the customers having slow internet connection problems and normal internet connection. We apply two classification approaches, multi perceptron neural networks and radial basis neural networks. Then, we cluster the same dataset using unsupervised techniques, namely Kohonnen{\textquoteright}s neural networks and Adaptive Resonance Theory neural networks. We evaluate the classification and clustering results using measures such as recall, accuracy and Davies-Bouldin index, respectively.",

keywords = "Artificial neural networks, Call center problem prediction, Classification, Clustering",

author = "Namlı, {{\"O}zge H.} and Seda Yanık and Faranak Nouri and {\c S}eng{\"o}r, {N. Serap} and Koyuncu, {Yusuf Mertkan} and İrem K{\"u}{\c c}{\"u}kali",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2020 ; Conference date: 21-07-2020 Through 23-07-2020",

year = "2021",

doi = "10.1007/978-3-030-51156-2_109",

language = "English",

isbn = "9783030511555",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "941--948",

editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Basar Oztaysi and Sari, {Irem Ucal} and Selcuk Cebi and Tolga, {A. Cagri}",

booktitle = "Intelligent and Fuzzy Techniques",

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Namlı, ÖH, Yanık, S, Nouri, F, Şengör, NS, Koyuncu, YM & Küçükali, İ 2021, Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Advances in Intelligent Systems and Computing, vol. 1197 AISC, Springer, pp. 941-948, International Conference on Intelligent and Fuzzy Systems, INFUS 2020, Istanbul, Turkey, 21/07/20. https://doi.org/10.1007/978-3-030-51156-2_109

Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach. / Namlı, Özge H.; Yanık, Seda; Nouri, Faranak et al.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A. Cagri Tolga. Springer, 2021. p. 941-948 (Advances in Intelligent Systems and Computing; Vol. 1197 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Improving Customer Experience for an Internet Service Provider

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2020

AU - Namlı, Özge H.

AU - Yanık, Seda

AU - Nouri, Faranak

AU - Şengör, N. Serap

AU - Koyuncu, Yusuf Mertkan

AU - Küçükali, İrem

PY - 2021

Y1 - 2021

N2 - Today one of the challenges of companies is to decrease call center costs while improving the customer experience. In this study, we make prediction and proactively take action in order to solve customer problems before they reach the customer call center. We use machine learning techniques and train models with a dataset of an internet service provider’s several different systems. We first use supervised techniques to classify the customers having slow internet connection problems and normal internet connection. We apply two classification approaches, multi perceptron neural networks and radial basis neural networks. Then, we cluster the same dataset using unsupervised techniques, namely Kohonnen’s neural networks and Adaptive Resonance Theory neural networks. We evaluate the classification and clustering results using measures such as recall, accuracy and Davies-Bouldin index, respectively.

AB - Today one of the challenges of companies is to decrease call center costs while improving the customer experience. In this study, we make prediction and proactively take action in order to solve customer problems before they reach the customer call center. We use machine learning techniques and train models with a dataset of an internet service provider’s several different systems. We first use supervised techniques to classify the customers having slow internet connection problems and normal internet connection. We apply two classification approaches, multi perceptron neural networks and radial basis neural networks. Then, we cluster the same dataset using unsupervised techniques, namely Kohonnen’s neural networks and Adaptive Resonance Theory neural networks. We evaluate the classification and clustering results using measures such as recall, accuracy and Davies-Bouldin index, respectively.

KW - Artificial neural networks

KW - Call center problem prediction

KW - Classification

KW - Clustering

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U2 - 10.1007/978-3-030-51156-2_109

DO - 10.1007/978-3-030-51156-2_109

M3 - Conference contribution

AN - SCOPUS:85088740782

SN - 9783030511555

T3 - Advances in Intelligent Systems and Computing

SP - 941

EP - 948

BT - Intelligent and Fuzzy Techniques

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

A2 - Tolga, A. Cagri

PB - Springer

Y2 - 21 July 2020 through 23 July 2020

ER -

Namlı ÖH, Yanık S, Nouri F, Şengör NS, Koyuncu YM, Küçükali İ. Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Springer. 2021. p. 941-948. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-51156-2_109

Improving Customer Experience for an Internet Service Provider: A Neural Networks Approach

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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