Machine Learning for Digital Advertising

When using TV, radio, or street banners for our company marketing, it is difficult to assess what in our campaign is working, and what is not. But when using digital marketing, we can access a large amount of information to identify what we are doing right and what we are doing wrong.

For a given user that clicks on our ad, we can find information such as: What was the appearance of the ad? Texts, words used, image, colours… What kind of user we targeted? Age, gender, location, language…
* Which experience we offered to the user? Appearance of the landing page, number of clicks required to achieve the goal, information requested in forms…

As advertisers, we have a lot of control on all these variables, we decide what is the UX of our site, the graphical design of our ads, the users that we are targeting… With some basic analysis we can easily identify which ad is performing better, which are the main market segments that buy our products, or which is the page layout that maximizes sales. But this is only a small part of what we can do, by tracking all the available information, mining it, and using machine learning to take the right decisions in real time.

View the presentation below to understand what is direct response digital marketing, which is the information available, and what makes digital marketing information different of other domain datasets.