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Enhancing customer satisfaction in telecommunications: a generative artificial intelligence chatbot analysis

datacite.subject.fosCiências Sociais::Economia e Gestãopt_PT
dc.contributor.advisorBelo, Rodrigo
dc.contributor.authorVidinha, Maria Miguel Sequeira
dc.date.accessioned2024-10-16T10:11:17Z
dc.date.embargo2027-12-20
dc.date.issued2024-01-26
dc.date.submitted2023-12-20
dc.description.abstractThis study, conducted in collaboration with a European telecommunications company, explores the impact of a Generative AI chatbot on customer satisfaction, a driver for customer retention. Using quantitative data methods and the descriptive properties of logistic regression, the research uncovers nuanced insights by analyzing shifts in customer behavior, technology effectiveness, and key factors influencing explicit customer feedback. Findings revealed a positive influence on customer satisfaction and uncovered the multifaceted nature of feedback, specifically regarding service complaints. It laid a foundation for data-driven decision-making towards future work being done in the dynamic landscape of customer interactions with the chatbot.pt_PT
dc.identifier.tid203605411pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/173564
dc.language.isoengpt_PT
dc.relationUID/ECO/00124/2013pt_PT
dc.subjectTelecommunications industrypt_PT
dc.subjectCustomer satisfactionpt_PT
dc.subjectChatbotpt_PT
dc.subjectGenerative aipt_PT
dc.subjectLogistic regressionpt_PT
dc.titleEnhancing customer satisfaction in telecommunications: a generative artificial intelligence chatbot analysispt_PT
dc.typemaster thesis
dspace.entity.typePublication
rcaap.rightsembargoedAccesspt_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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