Using Predictive Analytics to Overcome Enrollment Management … · 2020-03-14 · Predictive...
Transcript of Using Predictive Analytics to Overcome Enrollment Management … · 2020-03-14 · Predictive...
Using Predictive Analytics to Overcome Enrollment
Management Challenges
Alex HerbertSales Manager
Jon MacMillanSenior Data Analyst
February 26th, 2019
Agenda• Who We Are
• Enrollment Management Challenges
• Enrollment Modeling
• Retention Modeling
• Utilizing the Results
• Q & A
About Rapid Insight
Founded in 2002 and headquartered in Conway, NH
Predictive analytics and data preparation software company empowering professionals of all skill levels to turn raw data into actionable insights
Serving hundreds of customers worldwide, ranging from healthcare to higher education
The Veera platform enables users to easily build predictive models, perform advanced data analysis, and share insights
Code free (but code friendly)self-service analytics platform
Veera Construct enables everyone from citizen data scientists to PhD statisticians to turn any data into actionable information
Veera Predict enables users of any skill level to analyze data and build predictive models in a fraction of time required by other tools
Veera Bridge empowers organizations by democratizing data with its cloud-based collaboration platform
The Veera Platform
Using Predictive Analytics to Overcome Enrollment
Management Challenges
Enrollment Management/en•roll•ment man•age•ment/ [noun]
1. An organizational concept and a systematic set of activities designed to enable educational institutions to exert more influence over their student enrollments
Improve Yields
Grow Applicant Pool
Increase Net Revenue
Improve Retention
(Hossler & Bean, The Strategic Management of College Enrollments)
Enrollment Management ChallengesPercent Change From Previous Year, Enrollment by Sector
Term Enrollment Estimates Fall 2018 (https://nscresearchcenter.org)
Predictive Analytics in Enrollment Management
Enrollment Retention
Improve Yields
Grow Applicant Pool
IncreaseNet Revenue
Improve Retention
Predictive Analytics in Enrollment
•Qualify names
•Prioritize inquiry pool
•Optimize contact
•Run simulations
•Craft your class
• Lost applicants
Leads/Prospects
Inquiries
Applicants
Stealth Apps
Completed Apps
Admits
Enrolled
What is Predictive Analytics?= Enrolled
= Applied
Distance From Campus
Enrollment Likelihood
Common Enrollment Modeling Data Points
Common Enrollment Modeling Data Points
Common Enrollment Modeling Data Points
ConnectIntegrate data in any format, from virtually any source
PrepareCreate step-by-step processes using easy, drag-and-drop visual workflows with no coding required
AnalyzeBuild and schedule jobs to run automatically, or run on-demand analyses
ShareWrite back to databases, create and disseminate reports, publish dashboards to visual analytics tools such as Tableau, or output datasets for predictive modeling
Predictive Analytics in Retention• Early retention
• First year retention
• Term GPA
•Academic standing
•Graduation likelihood
•Persistence in major
Common Retention Modeling Data Points
Common Retention Modeling Data Points
Common Retention Modeling Data Points
Unique Retention Modeling Data Points
• Registration for classes
• Degree progress
• Academic marks
• Prerequisite course performance
• Final grades
• Interventions
• Campus engagement
• Survey data
• Organizational membership
• Student record hold
• Mid-term deficiency reports
• Low career clarity
Fully TransparentAll methods and calculations performed are easily viewable
Automated Data MiningIdentify statistically significant data variables without manual effort
Easy to UseNew users can build expert models within two hours of training
No Programming NeededUse simple pick lists instead of programming or custom command languages
Automated Modeling ProcessBrings complex data analyses and predictive model building to users of any skill level
Communicating Your ResultsStudent
IDEnrollment Probability
1115791 High
1112845 High
1119128 High
1112464 High
1122893 High
1107559 High
1115937 High
1104038 Medium
1122038 Medium
1122876 Medium
1108547 Medium
1111941 Medium
1113438 Medium
1109982 Medium
1117425 Low
1106681 Low
1114973 Low
1110257 Low
1111303 Low
Communicating Your ResultsStudent
IDEnrollment Probability
1115791 94.88%
1112845 92.20%
1119128 89.78%
1112464 87.70%
1122893 84.81%
1107559 83.27%
1115937 81.22%
1104038 76.03%
1122038 75.94%
1122876 74.39%
1108547 68.10%
1111941 58.71%
1113438 57.24%
1109982 51.33%
1117425 37.33%
1106681 27.90%
1114973 14.71%
1110257 8.26%
1111303 5.38%
Communicating Your ResultsStudent
IDEnrollment Probability
1115791 94.88%
1112845 92.20%
1119128 89.78%
1112464 87.70%
1122893 84.81%
1107559 83.27%
1115937 81.22%
1104038 76.03%
1122038 75.94%
1122876 74.39%
1108547 68.10%
1111941 58.71%
1113438 57.24%
1109982 51.33%
1117425 37.33%
1106681 27.90%
1114973 14.71%
1110257 8.26%
1111303 5.38%
Communicating Your ResultsStudent
IDEnrollment Probability Variable1
Variable1 Contribution Variable2
Variable2 Contribution
1115791 94.88%DaysBetween 71.1 % (+) Distance 16.15 % (+)
1112845 92.20%Distance 63.7 % (+) DaysBetween 23.39 % (+)
1119128 89.78%Distance 65.04 % (+) DaysBetween 21.77 % (+)
1112464 87.70%Distance 71.97 % (+) AppliedForFA 9.75 % (+)
1122893 84.81%MediaStudies 35.88 % (+) Distance 33.72 % (+)
1107559 83.27%MediaStudies 39.2 % (+) Distance 36.83 % (+)
1115937 81.22%SAT 30.2 % (+) Distance 21.84 % (+)
1104038 76.03%SAT 36.67 % (+) Distance 25.56 % (+)
1122038 75.94%DaysBetween 34.03 % (+) Distance 21.86 % (+)
1122876 74.39%Distance 36.48 % (+) AppliedForFA 19.25 % (+)
1108547 68.10%AppliedForFA 37.18 % (-) Distance 18.15 % (+)
1111941 58.71%SAT 36.89 % (-) AppliedForFA 32.67 % (+)
1113438 57.24%Distance 47.31 % (-) AppliedForFA 20.64 % (+)
1109982 51.33%SAT 23.48 % (-) Distance 20.79 % (-)
1117425 37.33%Distance 40.15 % (-) HS% 23.39 % (-)
1106681 27.90%Distance 58.44 % (-) EFC 11.87 % (-)
1114973 14.71%Distance 39.12 % (-) SAT 22.01 % (-)
1110257 8.26%Distance 70.42 % (-) EFC 7.86 % (-)
1111303 5.38%Distance 81.51 % (-) Undeclared 5.24 % (-)
Communicating Your ResultsStudent
IDEnrollment Probability
Explanation
1115791 94.88%This student applied later in the admissions cycle which increases their enrollment likelihood
1112845 92.20%This student lives near campus, which increases their enrollment likelihood
1119128 89.78%This student lives near campus, which increases their enrollment likelihood
1112464 87.70%This student lives near campus, which increases their enrollment likelihood
1122893 84.81%This student is not a Media Studies major, which increases their enrollment likelihood
1107559 83.27%This student is not a Media Studies major, which increases their enrollment likelihood
1115937 81.22%This student has lower SAT scores than average, which increases their enrollment likelihood
1104038 76.03%This student has lower SAT scores than average, which increases their enrollment likelihood
1122038 75.94%This student applied later in the admissions cycle which increases their enrollment likelihood
1122876 74.39%This student lives near campus, which increases their enrollment likelihood
1108547 68.10%This student did not apply for FA which decreases their enrollment likelihood
1111941 58.71%This student has higher SAT scores than average, which decreases their enrollment likelihood
1113438 57.24%This student lives farther from campus, which decreases their enrollment likelihood
1109982 51.33%This student has higher SAT scores than average, which decreases their enrollment likelihood
1117425 37.33%This student lives farther from campus, which decreases their enrollment likelihood
1106681 27.90%This student lives farther from campus, which decreases their enrollment likelihood
1114973 14.71%This student lives farther from campus, which decreases their enrollment likelihood
1110257 8.26%This student lives farther from campus, which decreases their enrollment likelihood
1111303 5.38%This student lives farther from campus, which decreases their enrollment likelihood
Total Predicted Enrollment
Student Type # of Students Predicted Yield Predicted Total
Admitted Applicants 4,207 46.23% 1,945
Continuing Students 4,256 78.64% 3,347
Total Enrollment 8,463 62.53% 5,292
Predictive Analytics in Practice
Enrollment Retention
• Optimized out-of-state recruitment
• Renewed focus on in-state recruitment
• Targeted faculty phone-a-thons
• Created buy-in
• Identified most at-risk students
• Faculty outreach and notification system
Results
• 5.7% increase in applicants
• 6.3% increase in confirms
• 4.5% increase in retention
+ =
Personalized Demo
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To schedule your personalized demo contact [email protected]
Questions?