Engaging Customers with Visual Generative AI

Abstract

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 whether fine-tuning generative AI directly on conventional advertising objectives like evoking attention or driving interest is possible. In this research, we 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. We also 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, we probe the limitations of aligning visual generative AI with marketing objectives.

Keywords: generative AI, digital marketing, advertising, consumer engagement, Deep Learning, Computer Vision