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A mi predictive model for customer churn at a b2b software company

datacite.subject.fosCiências Sociais::Economia e Gestãopt_PT
dc.contributor.authorBossé, Aliénor Alexia Désirée
dc.date.accessioned2024-09-24T13:25:19Z
dc.date.available2024-09-24T13:25:19Z
dc.date.issued2023-01-24
dc.date.submitted2023-01-24
dc.description.abstractThis paper proposes a machine learning model predicting customer churn at the studied B2B SaaS company. The model is based on a real-life dataset of the studied company’s active customers. The dataset considers various factors specific to B2B customers. The model is trained on this dataset and its performance is evaluated. The evaluation shows that data helps understanding some factors impacting the studied company’s customers’ behavior to churn. However, the quality of the available live data is questioned and will have to be tested in further iterations. Additionally, a new practice for customer churn management is derived from this analysis.pt_PT
dc.identifier.tid203316436pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/172303
dc.language.isoengpt_PT
dc.subjectCustomer churnpt_PT
dc.subjectChurn managementpt_PT
dc.subjectChurn predictionpt_PT
dc.subjectMachine learningpt_PT
dc.titleA mi predictive model for customer churn at a b2b software companypt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
thesis.degree.nameA Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics.pt_PT

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