Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/165797
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Campo DCValorIdioma
dc.contributor.advisorNeto, Miguel de Castro Simões Ferreira-
dc.contributor.advisorJardim, João Bruno Morais de Sousa-
dc.contributor.authorTrzos, Julia Marianna-
dc.date.accessioned2024-04-04T17:46:22Z-
dc.date.available2024-04-04T17:46:22Z-
dc.date.issued2024-01-31-
dc.identifier.urihttp://hdl.handle.net/10362/165797-
dc.descriptionInternship Report presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Digital Marketing and Analyticspt_PT
dc.description.abstractIn the ever-evolving landscape of modern banking, the incorporation of emerging technologies, specifically Artificial Intelligence and machine learning, holds great significance in order to remain relevant and efficiently address customer needs, having a potential for significant enhancements in customer relationship management practises within the banking industry. The objective of this project, conducted in collaboration with the Asseco PST Data & Analytics team, is to improve their CRM solution by incorporating a comprehensive machine learning framework. This involves utilising machine learning techniques to segment clients, with the goal of optimising customer relationship management (CRM) and providing data-driven campaigns for their bank clients. The project aims to develop a clustering-based Recommendation System that delivers customised product recommendations. Furthermore, the project presents a deployment demonstration involving the creation of apps aimed at achieving a scalable solution for clustering and predictive modelling, hence facilitating the implementation process for new clients. Additionally, this project intends to establish itself as an important component within Asseco PST's comprehensive offering. The integration of this work within their pre-existing CRM development offer serves to underscore its importance and possible influence within the constantly developing world of present-day banking.pt_PT
dc.language.isoengpt_PT
dc.rightsopenAccesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBusiness Intelligencept_PT
dc.subjectMachine Learningpt_PT
dc.subjectBankingpt_PT
dc.subjectCustomer Relationship Managementpt_PT
dc.subjectArtificial Intelligencept_PT
dc.subjectCustomer Segmentationpt_PT
dc.titleAI-driven Customer Analytics: Implementation of Machine Learning Solutions into bank’s CRMpt_PT
dc.typemasterThesispt_PT
thesis.degree.nameMestrado em Marketing Analítico, especialização em Marketing Digital e Análise de Dadospt_PT
dc.identifier.tid203568443pt_PT
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopt_PT
Aparece nas colecções:NIMS - Dissertações de Mestrado em Marketing Analítico (Data-Driven Marketing)

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