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Industry 4.0: predicting lead conversion opportunities with machine learning in small and medium sized enterprises

dc.contributor.authorGouveia, Luis Borges
dc.contributor.authorCOSTA, OBERDAN
dc.date.accessioned2022-03-15T16:40:26Z
dc.date.available2022-03-15T16:40:26Z
dc.date.issued2022-03-11
dc.description.abstractThe crisis caused by COVID-19 accelerated processes of changes in the global economy, leading to changes in companies in structures, business models and routines. Small and Medium Enterprises (SME) in particular have faced challenges in finding paths for the journey of digital transformation and adaptation to the industry 4.0 era, which turns integration a key factor. The goal of this work is to predict the likelihood of conversion using Machine Learning (ML), with the purpose of improving the process of converting opportunities in SME in the education sector. The work is based on the Digital Transformation Model for SME (MTD_PMEs), a specific approach in ML technology and Knowledge Discovery in Databases (KDD). The methodology involves a three-step sequence of the KDD_AZ process. Data were collected from a university center in southern Brazil. Results indicate that the 8 attributes used are relevant for forecasting lead conversion and that the chosen technique, Logistic Regression reached a gross precision of 100%, implying an increase in the conversion rate, time savings for the teams and filter leads “unlikely”, helping marketing improvements in its targeting and providing qualified leads.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.urihttp://hdl.handle.net/10284/10891
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectBusiness modelpt_PT
dc.subjectIndustry 4.0pt_PT
dc.subjectDigital transformationpt_PT
dc.subjectMachine learningpt_PT
dc.subjectSMEspt_PT
dc.titleIndustry 4.0: predicting lead conversion opportunities with machine learning in small and medium sized enterprisespt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceISLA, Vila Nova de Gaia, Portugalpt_PT
oaire.citation.titleInternational Conference On Industry Sciences and Computer Sciences Innovationpt_PT
person.familyNameManuel Borges Gouveia
person.familyNameCOSTA
person.givenNameLuis
person.givenNameOBERDAN
person.identifierxF1eGXcAAAAJ&hl
person.identifier.ciencia-id6B1C-3509-9FA5
person.identifier.orcid0000-0002-2079-3234
person.identifier.orcid0000-0002-2448-5247
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication5bca0222-5e07-4f60-91a0-25ac0242ae51
relation.isAuthorOfPublicationcb93a1f9-bd40-418e-a8aa-0a55e7c5157f
relation.isAuthorOfPublication.latestForDiscovery5bca0222-5e07-4f60-91a0-25ac0242ae51

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