Right in the context of digital marketing, this paper presents a comprehensive integrated system that combines the latest artificial intelligence advancement – large language models and diffusion models – to generate marketing email subjects and content that result in higher engagement. The system uses finetuned large language models for compelling email subject generation and finetuned Stable Diffusion model for visually appealing and convincing email content images creation. For the latter, both knowledge graphs and vector embeddings have been incorporated to improve contextual relevance. Experimental results demonstrated significant improvement in all engagement metrics that marketers rely on, including 46% growth in open rates, 56% higher click-through rates, and an 51% boost in conversion rates, all compared to human generated content. The unified approach presented by this paper outperforms standalone models and human-generated content in terms of engagement, as the comparative analysis shows. We also discuss the ethical considerations related to content bias and personalization boundaries, alongside challenges faced in this type of projects, such as computation demands and probable solutions. Finally, this paper proposes future directions to be taken, including expansion to other digital marketing channels, the use of other advanced artificial intelligence techniques, and the development of real-time content adaptation mechanisms based on user feedback.
Loukili et al. (Tue,) studied this question.
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