What is working in our creative?

Once thought futuristic and unlikely to happen in our lifetimes, the ability for computers to “see” has progressed exponentially in recent years. Machine learning algorithms are trained on millions of images and their labels, so that they can learn to recognize objects, faces, and landmarks. The technology can be used to automatically tag images with metadata, so that they can be easily searched and indexed. There are a range of applications from security and surveillance to image and video search, and decomposition analysis: breaking marketing creative down into its component parts to analyse what’s working.

Companies like Google and OpenAI have democratised these techniques through open source libraries and commercial APIs bringing the cost of experimenting with them down considerably. Now anyone can tag any image they like in a few seconds without owning a supercomputer or knowing anything about machine learning. Marketers who want to go a level deeper with creative analysis, can use computer vision to automatically tag each image used in an ad, and then pivot performance metrics to see what labels are correlated with your best and worst performing ads. Then these ideas can be used as new hypotheses to test in your creative testing plan, to validate if they work.