Leveraging Artificial Intelligence to Enhance Digital Marketing: An Analysis of Best Practices and Future Directions

Thesis title: Leveraging Artificial Intelligence to Enhance Digital Marketing: An Analysis of Best Practices and Future Directions
Author: Hakobyan, Diana
Thesis type: Diploma thesis
Supervisor: Mareš, Jan
Opponents: Hron, Michal
Thesis language: English
Abstract:
This master's thesis aims to comprehensively understand diverse AI models in digital marketing, empowering practitioners to enhance customer-brand engagement strategically. By bridging theory from the literature review and practical implementations from the in-depth expert interviews, it outlines specific AI tools, platforms, and applications, emphasizing advantages while addressing potential drawbacks. As a roadmap for future trends, the research examines ethical considerations, providing guidelines for responsible AI practices. The study concludes with practical recommendations to optimize AI adoption, contributing to advancing knowledge and aligning with global best practices in the field.
Keywords: machine learning; voice recognition; image recognition; natural language processing; artificial intelligence; digital marketing; deep learning; consumer decision making; ethics; consumer behavior
Thesis title: Leveraging Artificial Intelligence to Enhance Digital Marketing: An Analysis of Best Practices and Future Directions
Author: Hakobyan, Diana
Thesis type: Diplomová práce
Supervisor: Mareš, Jan
Opponents: Hron, Michal
Thesis language: English
Abstract:
This master's thesis aims to comprehensively understand diverse AI models in digital marketing, empowering practitioners to enhance customer-brand engagement strategically. By bridging theory from the literature review and practical implementations from the in-depth expert interviews, it outlines specific AI tools, platforms, and applications, emphasizing advantages while addressing potential drawbacks. As a roadmap for future trends, the research examines ethical considerations, providing guidelines for responsible AI practices. The study concludes with practical recommendations to optimize AI adoption, contributing to advancing knowledge and aligning with global best practices in the field.
Keywords: decision making; artificial intelligence; digital marketing; ethics; machine learning; consumer behavior; image recognition; natural language processing; voice recognition; deep learning

Information about study

Study programme: Management
Type of study programme: Magisterský studijní program
Assigned degree: Ing.
Institutions assigning academic degree: Vysoká škola ekonomická v Praze
Faculty: Faculty of Business Administration
Department: Department of Entrepreneurship

Information on submission and defense

Date of assignment: 1. 3. 2023
Date of submission: 13. 12. 2023
Date of defense: 29. 1. 2024
Identifier in the InSIS system: https://insis.vse.cz/zp/84306/podrobnosti

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