Maximize Enrollment Success Through Predictive Modeling

Liz Kistner - Monday, October 27, 2014

Is your prospect pool drying up?  Where are your prospects hiding? What does your ideal student look like demographically?  Answer these questions by building a foundation first-- a foundation built with data driven analytics.  Use analytics to maximize your student recruitment efforts through predictive modeling.    

Predictive Modeling uses your data to quantitatively predict the future behavior of an individual.  Modeling predicts:

  1. Non-student Prospecting: Determines the people who are most likely to enroll
  2. Student Prospecting (currently in your enrollment funnel): Determines the students who are mostly likely to enroll
  3. Student Loyalty: Determines those students who are at risk for attrition, and predicts student ROI

Modeling has two phases:

Phase One:  Segmentation Analysis.  The benefit of phase one is to obtain knowledge about the potential student through data profiling.  There are two ways to profile data:B2C or B2B.     B2C segmentation analysis provides information such as geography, household income, gender, marital status and presence of children.  B2B segmentation analysis provides profiles such as job title, employee size, buying authority, and industry type.  Learn how you can use segmentation analysis to gain insightful information that can be used in your marketing plans.  

Phase Two:  Statistical Modeling. This will help you find more potential students by using statistical algorithms. Use large databases to create a profile/look-alike model by comparing your client files against geographic, attitudinal, and/or behavioral-lifestyle attributes.   Profiling attributes my include work related segments (working part time, full time, unemployed, self employee), educational level, or motivating reasons why they want to go back to school (money, career advancement).

Predictive Modeling is essential to building a successful enrollment model.  Understanding your student’s demographics will help your school give you direction, efficiency and cost savings.  Universities are required to do more with less.  Can you really afford not to know?  Use the technology available to maximize your student recruitment efforts through predictive modeling.