Can AI (computer vision) help us to evaluate creatives at large scale?

Google Japan used a hybrid methodology of computer vision and human encoding to discover if artificial intelligence/machine learning could help it define good or bad ads in terms of driving business results.

Abstract

Can artificial intelligence/machine learning help us define what bad or good ads are in terms of driving business results? We demonstrate a hybrid methodology of computer vision and human encoding to conduct large-scale creative meta-analysis at a low cost. We also show how to design good prompts (input into a Generative AI model) to generate high-quality advertising. This new approach has the potential to help advertisers generate thousands of creatives to test for their campaigns. This could lead to significant improvements in advertising performance and ultimately help businesses achieve their marketing goals.

Introduction

Who isn't sick of bad ads...

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