Picture Perfect: Engaging Customers with Visual Generative AI
Mark Heitmann, Tijmen P.J. Jansen, Martin Reisenbichler, David A. Schweidel
Universität Hamburg NOVA School of Business and Economics Universidade Nova de Lisboa Vienna University of Economics and Business
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Generative artificial intelligence (AI) is poised to transform how brands communicate with consumers. Recent research demonstrates AI's benefits in producing text, but marketing research has not yet explored how marketers can leverage AI to create visual advertising. Despite their impressive capabilities, “off-the-shelf” generative AI models are not aligned with marketing objectives, raising the question of whether it is possible to fine-tune generative AI directly on conventional advertising objectives (e.g., evoking attention, driving interest). In this research, the authors train an open-source generative AI model on marketing mindset metrics and show that the resulting visual content can match and even exceed conventionally produced advertising content in associated performance metrics. The results demonstrate that generative AI can be fine-tuned on multiple communication objectives simultaneously and adapted to specific audiences. In addition to highlighting generative AI's potential in marketing, this article explores the limitations of aligning visual generative AI with marketing objectives.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
计算机 / AIPersona Design and Applications
Design Education and Practice · Innovative Human-Technology Interaction
参考文献 56
此处列出前 3 条
引用本文 21
按被引量排序,此处列出前 3 条