For the fourth and final installment in our impact series, I’d like to provide an example of how we are helping a key customer determine the quality of their name buys and the effectiveness of their sources. We’ve already reviewed examples of how we helped institutions tactically throughout the year through visit engagements and with their financial aid evaluations, and this example will show how we help our customers with their name buying and source evaluation at the very beginning of the enrollment cycle. I hope this final customer impact example resonates with you as you begin to plan for the 2020 enrollment class.

Surface Insights

Like many other institutions, our customer recognized that they had been purchasing an abundance of names to fill their prospect pool year-over-year. They began to question the quality of these prospects when they realized that purchasing more names didn’t necessarily result in more enrolled students. Additionally, they became curious if the yield from their purchased sources were artificially inflated due to overlap with other historically high-yield lead sources. Our customer tasked the Othot platform with analyzing every lead to uncover both their initial enrollment probabilities, as well as their predicted likelihood scores after progressing through the funnel.

Change Behavior

Our insights and analysis showed that approximately six percent of the purchased names resulted in applications, but only about one percent were predicted to enroll after being admitted. The Othot platform also confirmed that the majority of higher probability prospects entered the pool through a key source: a state operated platform for applying to all of public universities. This insight affirmed the institution’s decision to decrease their reliance and recruitment on leads from purchased lists as they began to budget and strategize for the next academic year.

Deliver Outcomes

The most important outcome is the improvement on recruiter efficiency. With thousands of leads to sift through, utilizing machine learning algorithms to know which individuals to prioritize is incredibly valuable. The recruitment team is also taking advantage of Othot’s capabilities for prescriptive analysis. They can quantify how much more likely each prospect would be to enroll if specific marketing activities are deployed. These efforts generated early indicators for increasing total enrollment while managing to their marketing and recruitment budget.

Continuously Improve

The source evaluation proved beneficial and we are working with our customer to understand key attributes of previously enrolled students to inform their purchase source requests. Since we can evaluate the likelihood to enroll across many characteristics, we can provide a deeper analysis of the most effective source of students.

Thank you for following our customer impact series over the last few weeks. I hope you gained valuable insight into how we are helping our great partners. The examples presented are just the tip of the iceberg in all the ways we are helping institutions. I’d welcome the opportunity to speak with you in more detail about the success we are achieving with our customers, so please reach out to me at if you have any further questions or if you’d like to begin working with an advanced analytics platform to achieve your enrollment and retention goals.