DC FieldValueLanguage
dc.contributor.authorGiovanis, Apostolos-
dc.contributor.authorFrangos, Christos-
dc.contributor.authorPapathanasiou, Dimitris-
dc.date.accessioned2024-06-14T12:55:18Z-
dc.date.available2024-06-14T12:55:18Z-
dc.date.issued2009-05-
dc.identifiergoogle_scholar-In1YXmwAAAAJ:WF5omc3nYNoC-
dc.identifier.isbn978-960-98739-0-1-
dc.identifier.issn1791-8499-
dc.identifier.otherIn1YXmwAAAAJ:WF5omc3nYNoC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2552-
dc.description.abstractCustomer churn and retention rates are considered as the most important indicators to CRM activities such as modelling customer valuation and budget allocation. Such models, which are trying to predict customer’s survival rate, assume that churn rates are constant both over time and across customers. The current practice, however, have shown that these assumptions are not valid and are currently tested in a systematic manner. The practice shows that churn propensity vary dramatically across customers and over time; yet, most models do not account for such differences. This study takes under consideration a number of factors that may underlie customer retention patterns. Specifically a model of mobile services’ retention is developed that takes into account: duration dependence, cross-cohort effects, customer heterogeneity, and contractual obligation type. Moreover, a methodology is proposed that easily allows practitioners to evaluate the relative importance of each of these effects based on in-sample and out-of-sample performance using limited information. Using a dataset from a major Greek telecommunication company concerning customers’ gross additions for twelve months and the relevant disconnections for the same time period ahead, two models on aggregate data at the monthly level are tested. The proposed modelling approach reveals that the notion of a constant churn rate is rejected. The representation of customer’s retention process requires all the proposed components listed above towards improving the retention and churn rate forecasting performance.en_US
dc.language.isoenen_US
dc.relation.ispartofProceedings of the 2nd International Conference "Quantitative and Qualitative Methodologies in the Economic and Administrative Sciences"en_US
dc.sourceProceedings of the 2nd International Conference: Quantitative and …, 2009-
dc.titlePredicting multi-cohort's customer retention using limited informationen_US
dc.typeConference Paperen_US
dc.relation.conference2nd International Conference "Quantitative and Qualitative Methodologies in the Economic and Administrative Sciences", 25-27 May 2009, Athens, Greeceen_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.identifier.spage173en_US
dc.identifier.epage178en_US
dc.linkhttps://books.google.com/books?hl=en&lr=&id=ri9ZK2nvl64C&oi=fnd&pg=PA173&dq=info:62i0SZ7OOFgJ:scholar.google.com&ots=g1iSeuAapa&sig=f3shAOWIQ2KLqx6JQL3XfdjGg4Uen_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.grantfulltextnone-
item.cerifentitytypePublications-
item.openairetypeConference Paper-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.languageiso639-1en-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.orcid0000-0003-1028-146X-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου
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