Let’s be real. We don’t know what we don’t know. Predicting anything in the future is difficult. It is especially complex when factors existing outside of your data can have a substantial influence on future behaviors.
Still, this doesn’t mean that your historical data aren’t informative. On the contrary. The COVID-19 pandemic is exactly the time you should lean on historical data and statistical predictions. Even if predictions are less certain than in earlier years, they are better than guessing.
Given the global scope of the COVID-19 pandemic, we hypothesize that, for the most part, students who were planning to go to college in 2020 will still go to college in 2020. Most will enroll at the institutions to which they have already applied and shown demonstrated interest. We will be testing this hypothesis, in real time, on the lead indicator of deposits as the 2020 admission cycle progresses, and we’ll modify our assumptions if the behavior of deposits changes.
At Capture, we are leveraging the most advanced technology in the industry, combined with decades of enrollment management experience, to assist you during these uncertain times:
- Students’ deposit behavior might look different over the next couple months but will remain an important leading indicator. Our machine learning models are built to leverage this behavioral data.
- Historically, visiting campus has been a powerful predictor of enrollment, but the utility of that measure for predicting 2020 enrollments changed mid-cycle after schools canceled their visit programs. Capture’s data science team has modified the coding of campus visit in our models to ensure that we’re only including visits that occurred before March, both historically and in the current year.
Our advice is to keep up the great work and stick to the fundamentals. Use predictive models to allocate resources. Focus yield efforts on students who are most likely to enroll. Pay attention to deposits.