Transforming Digital Marketing with Generative AI

Tasin Islam, Alina Miron, Monomita Nandy, Jyoti Choudrie, Xiaohui Liu, Yongmin Li

Research output: Contribution to journalArticlepeer-review

Abstract

The current marketing landscape faces challenges in content creation and innovation,
relying heavily on manually created content and traditional channels like social media and search
engines. While effective, these methods often lack the creativity and uniqueness needed to stand
out in a competitive market. To address this, we introduce MARK-GEN, a conceptual framework
that utilises generative artificial intelligence (AI) models to transform marketing content creation.
MARK-GEN provides a comprehensive, structured approach for businesses to employ generative AI
in producing marketing materials, representing a new method in digital marketing strategies. We
present two case studies within the fashion industry, demonstrating how MARK-GEN can generate
compelling marketing content using generative AI technologies. This proposition paper builds
on our previous technical developments in virtual try-on models, including image-based, multipose, and image-to-video techniques, and is intended for a broad audience, particularly those in
business management
Original languageEnglish
Article number168
Pages (from-to)1-24
Number of pages24
JournalComputers
Volume13
Issue number7
Early online date8 Jul 2024
DOIs
Publication statusE-pub ahead of print - 8 Jul 2024

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