Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/29338
Title: Transforming Digital Marketing with Generative AI
Authors: Islam, T
Miron, A
Nandy, M
Choudrie, J
Liu, X
Li, Y
Keywords: generative AI;deep learning;e-commerce;digital marketing
Issue Date: 8-Jul-2024
Publisher: MDPI
Citation: Islam, T. et al. (2024) 'Transforming Digital Marketing with Generative AI', Computers, 13 (7), 168, pp. 1 - 24. doi: 10.3390/computers13070168.
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, multi-pose, and image-to-video techniques, and is intended for a broad audience, particularly those in business management.
Description: Data Availability Statement: This paper did not generate any new data.
The repositories for the projects are as follows: https://github.com/1702609/SVTON; https://github.com/1702609/FashionFlow (accessed on 6 July 2024).
URI: https://bura.brunel.ac.uk/handle/2438/29338
DOI: https://doi.org/10.3390/computers13070168
Other Identifiers: ORCiD: Tasin Islam https://orcid.org/0000-0001-7568-9322
ORCiD: Alina Miron https://orcid.org/0000-0002-0068-4495
ORCiD: Monomita Nandy https://orcid.org/0000-0001-8191-2412
ORCiD: Jyoti Choudrie https://orcid.org/0000-0001-9349-7690
ORCiD: Xiaohui Liu https://orcid.org/0000-0003-1589-1267
ORCiD: Yongmin Li https://orcid.org/0000-0003-1668-2440
Appears in Collections:Dept of Computer Science Research Papers
Brunel Business School Research Papers

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