You know which creatives are performing, but do you know why? For that you have to look at what’s IN the creative, to see what’s really driving performance.
Analysing what attributes of your creative are working, usually means tagging hundreds of images manually...More
To see what attributes of our creative are working we have to tag them with what’s in the image
But I don’t think that’s realistic given we’ve tested hundreds of ads
I have an idea though
Why don’t we use Google Vision to tag the images for us?
AI is getting pretty good, and we wouldn’t have to do all this manually and can get insights right away
When we launch new creative we just need to run the script again to tag it
It could even be set up as a fully automated report
Do you want to check it out and see how it works?
This course is a work of fiction. Unless otherwise indicated, all the names, characters, businesses, data, places, events and incidents in this course are either the product of the author's imagination or used in a fictitious manner. Any resemblance to actual persons, living or dead, or actual events is purely coincidental.
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.
Complete all of the exercises first to receive your certificate!
Share This Course