{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T15:36:52Z","timestamp":1787499412643,"version":"build-2736575974"},"reference-count":43,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T00:00:00Z","timestamp":1647388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.<\/jats:p>","DOI":"10.3390\/fi14030094","type":"journal-article","created":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T22:09:58Z","timestamp":1647468598000},"page":"94","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":55,"title":["A Data-Driven Approach to Improve Customer Churn Prediction Based on Telecom Customer Segmentation"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1852-5094","authenticated-orcid":false,"given":"Tianyuan","family":"Zhang","sequence":"first","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o em Ci\u00eancias da Informa\u00e7\u00e3o, Tecnologias e Arquitetura (ISTA), Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), ISTAR, 1649-026 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4861-6686","authenticated-orcid":false,"given":"S\u00e9rgio","family":"Moro","sequence":"additional","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o em Ci\u00eancias da Informa\u00e7\u00e3o, Tecnologias e Arquitetura (ISTA), Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), ISTAR, 1649-026 Lisbon, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9841-9720","authenticated-orcid":false,"given":"Ricardo F.","family":"Ramos","sequence":"additional","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o em Ci\u00eancias da Informa\u00e7\u00e3o, Tecnologias e Arquitetura (ISTA), Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), ISTAR, 1649-026 Lisbon, Portugal"},{"name":"Instituto Polit\u00e9cnico de Coimbra, ESTGOH, Rua General Santos Costa, 3400-124 Oliveira do Hospital, Portugal"},{"name":"CICEE\u2014Centro de Investiga\u00e7\u00e3o em Ci\u00eancias Econ\u00f3micas e Empresariais, Universidade Aut\u00f3noma de Lisboa, Rua de Santa Marta, Pal\u00e1cio dos Condes do Redondo, 56, 1169-023 Lisboa, Portugal"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Peji\u0107 Bach, M., Pivar, J., and Jakovi\u0107, B. 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