The Hong Kong Polytechnic University & Think China - Research on AI-Enhanced Creative Copy for Women's Skincare Products
Company overview
SOLARIS ASIA PACIFIC VENTURES LIMITED is the client and research sponsor for this project, focusing on specialized research in AI-assisted content creation, brand communication, and youth-oriented creative expression. During project execution, Kai Feimoy Technology (Shenzhen) Co., Ltd. collaborated with the Business School of The Hong Kong Polytechnic University to launch a co-creation campaign for the su:m37° Water-Soaking Series, engaging university students in brand copywriting activities. The su:m37° Water-Soaking Series centers on skin hydration and moisture-based skincare scenarios. This project connects real-world brand communication tasks with AI applications, youth creative expression, and marketing content research, providing a practical research context for evaluating the actual value of generative AI in brand content production.
Research background
Generative AI is increasingly being applied in advertising strategy, social media operations, and marketing copywriting. However, differences may exist among various AI tools in understanding brand information, creative expansion, expression styles, and content generation efficiency. The actual effectiveness of AI-assisted versus fully manual creation still requires validation under standardized tasks. To better understand the impact of AI participation on youth creative performance, this project sets a specific task—creating a Xiaohongshu (Little Red Book) brand post—under uniform brand context, product features, target audience, and creative guidelines. It compares the performance of AI-assisted and fully manual groups across dimensions such as creative quality, content style, brand alignment, and completion efficiency, providing real-world data support for brand marketing applications and related academic research.
Research scope
In May 2026, CEIDEA Research was commissioned by SOLARIS ASIA PACIFIC VENTURES LIMITED to conduct a study on AI-assisted creative copy for the su:m37° Water-Soaking Series, employing a hybrid approach combining online surveys and group creative experiments. The study recruited, verified, and engaged undergraduate students from key universities, collecting data on task execution and final outputs. Participants with experience in marketing, new media operations, content creation, or literary writing, as well as those without such experience, were included. Additionally, data on AI usage habits, creative attitudes, brand awareness, and personal attributes were collected. Participants completed the Xiaohongshu copywriting task under uniform timeframes, brand materials, creative instructions, and incentive mechanisms. The AI-assisted group used a designated model for human-AI collaboration, while the fully manual group independently completed the task. The project documented final copy, AI interaction processes, and relevant background variables, and implemented quality control measures—including student ID verification, campus information, location data, device logs, response duration, questionnaire logic, and text completeness—to establish a reliable dataset for comparing the performance of different creation methods.
Expected outcomes
The project is expected to produce a comprehensive dataset comprising creative copy outputs, participant background information, and human-AI interaction records. The study will systematically evaluate the performance of AI-assisted and fully manual creation in terms of creative quality, expression style, brand alignment, content differentiation, and production efficiency. It will also identify the influence of writing experience, AI usage patterns, and individual characteristics on the final creative outcomes. The research findings will support the selection of high-quality content aligned with the su:m37° Water-Soaking Series' communication needs, optimize Xiaohongshu content strategies tailored to younger audiences, and help project stakeholders determine the appropriate applications of generative AI in brand marketing, consumer co-creation, and content production. The dataset will provide sustainable, actionable support for future model development, communication strategy refinement, and academic research.
Scan to add our research consultant