发表机构
University of Bayreuth; Fraunhofer FIT（拜罗伊特大学; 弗劳恩霍夫应用信息技术研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对AI广告图像个性化空白，提出基于客户数据的生成框架，经100人实验发现中等个性化效果最佳，高度个性化虽提升感知个性化但怪异感主导负面效应。
AI 中文摘要
传统个性化营销将静态产品与客户匹配，而动态创意优化主要侧重于AI驱动的文本个性化或基本的产品图像修改。我们通过开发和实施一个基于AI的框架来弥补这一差距，该框架直接根据客户数据生成个性化广告图像。我们在一个两阶段受试者内研究中评估该框架，涉及N=100名参与者、四种产品和三个个性化水平，这些水平根据所使用的客户数据的数量和具体性而变化。参与者对每张图像在广告态度、产品态度和购买意愿方面进行评分。结果表明，参与者感知到不同个性化水平之间的差异，并在中等个性化水平下对AI生成的广告图像评价最为积极。高度个性化增加了感知个性化，这与所有三个结果指标呈正相关，但也增加了感知怪异感，后者与结果呈负相关并主导总效应。
英文摘要
Personalized marketing traditionally matches static products to customers, while dynamic creative optimization focuses mainly on AI-driven text personalization or basic product image modifications. We address this gap by developing and implementing an AI-based framework that generates personalized advertising imagery directly from customer data. We evaluate this framework in a two-stage within-subject study with N=100 participants across four products and three levels of personalization, varied by the amount and specificity of customer data used. Participants rated each image on attitude toward the advertisement, attitude toward the product, and purchase intention. Results show that participants perceive differences across personalization levels and evaluate AI-generated advertising imagery most positively at a moderate level of personalization. High personalization increases perceived personalization, which is positively associated with all three outcome measures, but also increases perceived creepiness, which is negatively associated with the outcomes and dominates the total effect.
