创造力
晋升(国际象棋)
相关性(法律)
计算机科学
可扩展性
在线广告
用户参与度
广告
人工智能
万维网
业务
心理学
互联网
政治学
社会心理学
数据库
政治
法学
作者
John Douglas Hunt,Deborah A. Kerr
摘要
In an era where artificial intelligence (AI) integration into marketing strategies is becoming increasingly prevalent, this study examines the efficacy of AI-generated advertising copy against human-written copy. Focusing on a diverse range of businesses, including podcast promotion, dental marketing, restaurant advertising, real estate investment, SaaS tool promotion and sports team engagement, the research employs rigorous A/B testing methodologies. Metrics for comparison included click-through rates (CTRs) and cost per result across ad campaigns optimised for web traffic and engagement on the Meta platform. Different AI models, such as GPT-4, Custom GPT for Meta Ads and Meta’s own AI suggestions, were tested alongside human copywriters. The findings reveal that while AI can efficiently generate ad copy that competes closely with human efforts, human copywriters consistently achieved higher CTRs and lower costs per result in the majority of tested scenarios. Human-generated copies outperformed AI in 9 out of 12 cases for cost-effectiveness and in 5 out of 12 cases for CTR effectiveness. These results underscore the nuanced understanding and creative capabilities that human marketers bring to ad copywriting, which are crucial in crafting compelling marketing messages that resonate with target audiences. This paper recommends a hybrid approach, leveraging AI’s ability to generate initial ad copy drafts and utilising human expertise for final edits and enhancements. This approach harnesses the speed and scalability of AI while ensuring the emotional and contextual relevance that only human creativity can provide, thus optimising both engagement and economic efficiency in digital advertising campaigns.
科研通智能强力驱动
Strongly Powered by AbleSci AI