Optimizing media campaigns by machine learning and 1st-party data

Many universities and institutions execute media campaigns in the hopes of generating enrollments. It is very common for enrollments to occur weeks, if not months after a click. Additionally, many platforms have a limited attribution lookback window that is much shorter than typical enrollments. Because of this, most institutions have media campaigns optimizing towards a conversion event which has a very poor conversion rate to eventual enrollment. Such events include form submissions to request information, starting an application, etc.

In this session, you will learn how Arizona State University is able to optimize media campaigns working across OPM and agency partners to leverage machine learning models built on 1st-party behavioral data. We’ll cover the basic roadmap to implementation, how-tos, and pitfalls that we’ve learned on our own roadmap to successful deployment.


Shruthi Jagannath — Arizona State University ( ASU )

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