Rosli, Nurul Fazleen (2024) The impact of artificial intelligence in firms’ marketing perfomance. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)
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Abstract
This study investigates the impact of artificial intelligence (AI) on high-tech marketing, aiming to assess its effectiveness and implications for businesses within this industry. Despite widespread attention to AI in various sectors, its specific influence on marketing strategies in the high-tech sector remains largely unexplored. This research seeks to bridge this knowledge gap by examining how AI shapes high-tech marketing, exploring both its advantages and disadvantages. The study focuses on customer segmentation, predictive analytics for lead generation, chatbots, personalized recommendations through virtual assistants, and sales forecasting, offering insights to enhance marketing strategies. The research questions revolve around understanding the overall impact and effectiveness of AI in different facets of high-tech marketing. While acknowledging the limitations in terms of algorithmic equality, emotional connection, data privacy, and technological complexity, the study emphasises the importance of its findings. The study could lead to substantial improvements in customer experiences, better segmentation tactics, and data-driven decision-making automate routine tasks, provide a competitive advantage, and drive innovation in the high-tech marketing landscape. By effectively leveraging AI technologies, high-tech marketers can personalize customer experiences, optimize marketing efforts, and achieve sustainable business growth in an industry marked by rapid evolution
Item Type: | Final Year Project (Project Report) |
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Uncontrolled Keywords: | Artificial intelligence, Firms', Marketing, High technology, Perfomance |
Subjects: | H Social Sciences > H Social Sciences (General) H Social Sciences > HF Commerce |
Divisions: | Library > Final Year Project > FPTT |
Depositing User: | Norfaradilla Idayu Ab. Ghafar |
Date Deposited: | 19 Nov 2024 07:33 |
Last Modified: | 19 Nov 2024 07:33 |
URI: | http://digitalcollection.utem.edu.my/id/eprint/32375 |
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