INNOVATIVE APPROACHES TO DESIGNING ARTIFICIAL INTELLIGENCE SYSTEMS FOR PERSONALIZED VIDEO CONTENT GENERATION IN SMM MANAGEMENT
Abstract
Objective. The objective of this scientific article is to develop a methodological framework and determine optimal approaches for implementing artificial intelligence (AI) systems in the generation of personalized video content for social media marketing (SMM). The research addresses challenges related to audience engagement and content personalization, aiming to enhance the efficiency and scalability of AI-driven video production. Methods. This scientific article employs a comparative analysis of AI-based video generation tools, assessing their effectiveness at different production stages. The methodology includes a literature review on AI integration in digital marketing, an evaluation of AI models such as ChatGPT, Claude AI, Midjourney, Runway, Kling, Magnific AI, Freepik AI, and CapCut for their applicability in video production, an analysis of prompt engineering techniques to optimize video generation quality, the use of competitor analysis tools such as BuzzSumo, Social Blade, Vidooly, and Noxinfluencer, and an experimental validation of AI-based video enhancement and editing methods, including Adobe Firefly, KreaAI, and Topaz AI. Results. The article presents a structured approach to AI-driven video production. Results indicate Claude AI is optimal for idea generation and scriptwriting, ChatGPT excels in prompt engineering, and Midjourney leads in image generation. Runway and Kling outperform in video synthesis, while Magnific AI and Freepik AI enhance quality. CapCut and Topaz AI provide effective video editing solutions. The research also formulates an optimal prompt structure for AI-based video generation. Scientific novelty. The novelty of this scientific article lies in its systematic integration of AI technologies for personalized video marketing. It introduces a structured methodology for AI prompt engineering and a competitive intelligence model for assessing AI-generated promotional content effectiveness. Practical significance. The findings offer direct applications in digital marketing, enabling businesses to reduce production costs and accelerate content deployment. The proposed framework allows marketers to leverage AI for automated scriptwriting, image generation, animation, and dubbing, optimizing engagement and conversion rates in SMM strategies.
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