Trace-Aware Workflows for Co-Creating Branded Content with Generative AI
Taehyun Yang, Eunhye Kim, Zhongzheng Xu, Fumeng Yang

TL;DR
This paper investigates how small-business owners create branded social media content using generative AI and proposes a trace-aware workflow system to support iterative content refinement.
Contribution
It introduces a prototype that scaffolds brand articulation, supports feedback exploration, and maintains a traceboard to improve AI-assisted content creation workflows for SBOs.
Findings
Identified challenges in translating brand 'feel' into prompts
Developed a trace-aware prototype to support iterative refinement
Demonstrated how process traces aid in content exploration and refinement
Abstract
Generative AI tools have lowered barriers to producing branded social media images and captions, yet small-business owners (SBOs) still struggle to create on-brand posts without access to professional designers or marketing consultants. Although these tools enable fast image generation from text prompts, aligning outputs with a brand's intended look and feel remains a demanding, iterative task. In this position paper, we explore how SBOs navigate iterative content creation and how AI-assisted systems can support SBOs' content creation workflow. We conducted a preliminary study with 12 SBOs who independently manage their businesses and social media presence, using a questionnaire to collect their branding practices, content workflows, and use of generative AI alongside conventional design tools. We identified three recurring challenges: (1) translating brand "feel" into effective…
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