OPTIMIZACIÓN DE CAMPAÑAS DE MARKETING CON ESTRATEGIAS DE NEUROMARKETING DESARROLLADAS POR INTELIGENCIA ARTIFICIAL
dc.contributor.author | Aguado Alvarez, Ivan | |
dc.date.accessioned | 2024-12-03T11:00:03Z | |
dc.date.available | 2024-12-03T11:00:03Z | |
dc.date.issued | 2024-11-29 | |
dc.identifier.uri | https://hdl.handle.net/10115/42272 | |
dc.description | Trabajo Fin de Grado leído en la Universidad Rey Juan Carlos en el curso académico 2024/2025. Directores/as: Francisco Antonio Serrano Acitores | |
dc.description.abstract | The following study addresses one of the most significant opportunities and challenges currently facing the field of marketing: the optimisation of marketing campaigns. In a context where consumers are increasingly saturated with information and, at the same time, demand personalised experiences, companies face the challenge of capturing their attention in an effective and meaningful way. This project is concerned with the potential of advanced neuromarketing technologies to enhance consumer interaction through the use of AI tools for the analysis and real-time response to users' emotional and cognitive responses. In light of the constraints imposed by conventional methodologies, there is a pressing need for novel approaches that can facilitate a more profound comprehension of consumer emotions and preferences. The combination of neuroscience and marketing knowledge, known as neuromarketing, is positioned as a key tool for understanding consumer behaviours. When integrated with artificial intelligence, it allows large volumes of data to be processed in an automated way and patterns to be extracted that reveal how consumers react to different advertising stimuli. This enables real-time personalisation of campaigns and the creation of more relevant experiences, contributing to a more authentic and lasting connection between brands and their audiences. The objective of this project is to develop a tool that can integrate neuromarketing and artificial intelligence in order to optimise marketing campaigns in real time. This will entail measuring the emotional response of users and adjusting strategies automatically. This initiative aims to enhance the efficacy of marketing campaigns while offering an innovative approach that benefits both companies and consumers, particularly in an environment where competition and technology are advancing rapidly. This project, therefore, represents an opportunity to apply the knowledge acquired throughout the course of study to a practical solution that responds to the trends and demands of today's marketing. | |
dc.language.iso | eng | |
dc.publisher | Universidad Rey Juan Carlos | |
dc.rights | ||
dc.rights.uri | ||
dc.subject | Advertising Metrics | |
dc.subject | AI (Artificial Intelligence) | |
dc.subject | Audience Personalization | |
dc.subject | Brand Loyalty | |
dc.subject | Campaign Effectiveness | |
dc.subject | Cognitive Impact | |
dc.subject | Consumer Behavior | |
dc.subject | Consumer Fatigue | |
dc.subject | Customer Engagement | |
dc.subject | Data Analysis | |
dc.subject | Data-Driven Decisions | |
dc.subject | Emotional Connection | |
dc.subject | Emotional Responses | |
dc.subject | Machine Learning | |
dc.subject | Marketing Strategy | |
dc.subject | Neuromarketing | |
dc.subject | Personalized Experiences | |
dc.subject | Predictive Modeling | |
dc.subject | Real-time Optimization | |
dc.subject | ROI (Return on Investment) | |
dc.title | OPTIMIZACIÓN DE CAMPAÑAS DE MARKETING CON ESTRATEGIAS DE NEUROMARKETING DESARROLLADAS POR INTELIGENCIA ARTIFICIAL | |
dc.type | info:eu-repo/semantics/studentThesis | |
dc.rights.accessRights | info:eu-repo/semantics/embargoedAccess |
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