Predictive Modeling
Make positive changes to your student recruitment and retention strategies by utilizing data to drive decisions. Through Hobsons' predictive modeling, you can truly maximize and focus your resources by understanding historical student information to predict future enrollment and retention behaviors. Given the current economy it is essential that all institutions ensure that they are taking advantage of all the resources they currently have available on campus.
A statistical predictive model is made up of a number of indicators, including a student's demographics, geographic location, test scores, high school GPA, family income, and other relevant factors specific to your institution. Predictive models can be made to statistically find which students are likely to just search for an institution, make a deposit, enroll, enroll for a second year, and graduate from an institution.
Predictive models are unique to every institution and combining the models with research can forecast success in enrollment and retention.
Unique—Each predictive model is set up to highlight what matters most at an individual institution.
Inclusive—As retention and recruitment experts, Hobsons helps our clients understand exactly what are all the factors that may affect attrition rates, whether they are obvious or not.
Comparative—With predictive modeling, institutions have the ability to compare year-on-year data. Thus, allowing them to understand what retention efforts are working on their campuses.
