Designing with AI for Digital Marketing
We present an interactive user interface that allows digital marketing professionals to have real time access to insights from a back end AI that predicts potential click through rates of composed content based on similar past campaigns. We wanted to investigate the extent to which digital marketing professionals would find our system usable and useful and whether or not the advice our system generated would create content that had higher click through rates than content developed without the system's advice. Our framework decomposes aspects of prior campaigns into features including image quality, memorability, and placement; and text readability, formality and sentiment. We show our algorithm has high predictive value on a historical test set (AUC .80) that digital marketing professionals give the system an overall high satisfaction rating and that, using the advice of the AI agent, we can generate content that creates up to 22% click through rate lift on a 700 A/B preference tasks given to master workers on AMT.
UMAP