Optimizing Call-to-Action Strategies with Human-AI Collaboration: Insights from Health Campaign Messaging

This study explores the effectiveness of human- and AI-generated messaging in blood donation campaigns, focusing on empathetic and urgent communication styles. Using a two-phase methodology, BERT-based text classification was employed to categorize campaign messages into their call-to-action type, followed by two-way ANOVA analysis to assess the impact of crafting style (Human, GenAI, Human+GenAI) and call-to-action type (empathetic vs. urgent) on donor engagement. The findings demonstrate that campaigns crafted by Human+GenAI teams significantly outperformed those created solely by humans or AI across all metrics, including subscribers, actual donors, new donors, and repeat donors. Empathetic messaging was particularly effective for attracting new donors, while urgent messaging resonated more with repeat donors, especially when optimized by Human+GenAI collaboration. These results suggest that combining human creativity with AI-driven optimization creates the most effective health communication strategies, offering valuable insights for future blood donation campaigns.