LLM生成广告在说服力上超越人类，尤其擅长权威与共识策略。
LLM-Generated Ads: From Personalization Parity to Persuasion Superiority
- 用人格特质和心理原则生成个性化广告，对比人类创作效果。
- AI广告整体偏好率达59.1%，在权威与共识策略上分别达63.0%和62.5%。
- 即使被识别为AI生成，仍有29.4%用户选择，适合大规模高效营销场景。
随着大语言模型（LLMs）生成说服性内容能力增强，理解其在不同广告策略中的表现至关重要。本文通过两部分研究，从人格化与心理说服两个角度考察LLM生成广告的效果。第一项研究（n=400）测试了基于开放性和神经质性的个性化广告生成能力，结果显示LLM生成广告与人类专家作品在吸引力上无显著差异（51.1% vs. 48.9%，p > 0.05），匹配人格时表现一致。第二项研究（n=800）转向普遍性说服策略，检验四种心理原则：权威、共识、认知与稀缺性。结果表明，AI生成广告显著优于人类创作（偏好率59.1%对40.9%，p < 0.001），其中权威（63.0%）与共识（62.5%）策略表现最佳。定性分析显示，AI更擅长构建复杂、具理想化的叙事，并实现视觉-叙事高度协调。关键的是，即使扣除21.2个百分点的识别惩罚后，AI广告仍胜出，且29.4%参与者明知其为AI生成仍选择。这表明LLM已从个性化平价进化至说服力优势，结合其近乎零边际成本和快速生成能力，对广告实践具有重大意义。
原文摘要 · Abstract (English)
As large language models (LLMs) become increasingly capable of generating persuasive content, understanding their effectiveness across different advertising strategies becomes critical. This paper presents a two-part investigation examining LLM-generated advertising through complementary lenses: (1) personality-based and (2) psychological persuasion principles. In our first study (n=400), we tested whether LLMs could generate personalized advertisements tailored to specific personality traits (openness and neuroticism) and how their performance compared to human experts. Results showed that LLM-generated ads achieved statistical parity with human-written ads (51.1% vs. 48.9%, p > 0.05), with no significant performance differences for matched personalities. Building on these insights, our second study (n=800) shifted focus from individual personalization to universal persuasion, testing LLM performance across four foundational psychological principles: authority, consensus, cognition, and scarcity. AI-generated ads significantly outperformed human-created content, achieving a 59.1% preference rate (vs. 40.9%, p < 0.001), with the strongest performance in authority (63.0%) and consensus (62.5%) appeals. Qualitative analysis revealed AI's advantage stems from crafting more sophisticated, aspirational messages and achieving superior visual-narrative coherence. Critically, this quality advantage proved robust: even after applying a 21.2 percentage point detection penalty when participants correctly identified AI-origin, AI ads still outperformed human ads, and 29.4% of participants chose AI content despite knowing its origin. These findings demonstrate LLMs' evolution from parity in personalization to superiority in persuasive storytelling, with significant implications for advertising practice given LLMs' near-zero marginal cost and time requirements compared to human experts.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。