making data driven decisions to increase net tuition revenue analytics enroll… · landscape of...
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Making Data Driven Decisions to
Increase Net Tuition Revenue
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+ Introduction + The State of Net Tuition Revenue + Big Data Analytics + What Gets Measured Gets Managed + An Example of A Big Data Analytics Technology Platform + Using Big Data Analytics to Impact Retention
TODAY’S AGENDA
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The State of Net Tuition Revenue
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Declining Enrollment or Missed Targets
Increase in Discounts
Increase in Financial Aid
Causes For a Drop in Net Tuition Revenue
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How to Combat Declining Net Tuition Revenue?
63% of higher education institutions did not meet their new student enrollment goals in
the prior year.*
INCREASE ENROLLMENT
In 2016-17, estimated average net tuition revenue per full-time freshman increased by
0.4 percent…outpaced by the rate of inflation which was 1.8 percent in the 2016
fiscal year.**
OPTIMIZE REVENUE PER STUDENT
Sources: *2015 INSIDE HIGHER ED SURVEY OF COLLEGE & UNIVERSITY ADMISSIONS DIRECTORS. - **Inside Higher Ed – Discounts Keep Climbing
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Big Data Analytics
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One Solution: Use Big Data Analytics to get more “best fit” students for
your institution while maximizing net tuition revenue and shaping the class
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Every two days, humans produce the same amount of data that they created cumulatively from the beginning of time to 2003.
Source: Miller & Chaplin 2013
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The Center of Machine Learning is Big Data Analytics + Leverages many internal and
external data sources + Enables you to predict a granular
outcome based on that data
+ Drives “prescriptions” that allow you to optimize a desired outcome
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Descriptive Analytics
Valu
e
Difficulty
What happened?
Why did it happen?
What will happen?
How can we make it happen?
Hindsight
Insight
Foresight
How Machine Learning is Different
Descriptive Analytics
Diagnostic Analytics
Predictive Analytics
Prescriptive Analytics
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Personalized Success
Alumni Engagement Enroll
Retain/Graduate
Maximize Success for the Institution and its Students Data and technology help prescribe personalized outcomes for each student
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Big Data Analytics – Lessons from Industry
of organizations surveyed believe big data analytics will redefine the competitive landscape of their industries within the next three years
89%
87%
*Source: ACCENTURE & GENERAL ELECTRIC STUDY, 2014
Also believe that failure to adopt a big data analytics strategy could cause an organization to lose both market share and momentum*
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What Gets Measured Gets Managed
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Acquisition of Students
Effectiveness of Marketing
Quality of Class
4 Things to Measure to Reach Your Goal
Net Tuition Revenue
$
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Acquisition of Students
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View Each Individual’s Likelihood to Enroll And Which Factors Contributed to Their Score
7% 65% 24% 1%
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+ Mail a Viewbook
+ Meet with a Field Counselor
+ Digital Marketing
+ Campus Visit
+ Financial Aid Offer
Change The Outcome Run What-If’s to see which students will be most impacted by your marketing actions
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Effectiveness of Marketing
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“I have an inquiry pool of 35,000 names and a print marketing budget of $190,000. I’d like to print: + 15,000 Viewbooks + 15,000 campus visit pieces + 5000 each of a 6-postcard series + 2000 invitations to our Open House. “Which students should get which? And how many students will enroll as a result?”
Make Data Driven Decisions to Maximize Your Marketing Dollars
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Knowing an Individual’s Top Influencers Helps Target Your Marketing Efficiently
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Quality of Class
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+ Have an Online Presence
+ Easily spot students with the
attributes you want to build into
the class
+ See which have the highest
probability of enrolling
+ Run “What-If?” scenarios to see
how to increase the probability
of a student enrolling
Shape Your Class
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Use What-If Prescriptives to Shape the Class We start with a prediction of enrolling just 50 students from NJ with SATs over 1300. What if they came for a spring visit?
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Use What-If Prescriptives to Shape the Class If they all came for a spring visit, we’d enroll 221. Othot shows who’s spring visit to fund by showing which students will be impacted the most.
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Net Tuition Revenue
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1/3
Othot’s Platform showed a partner institution that for 33% of the
students to whom they offered merit aid, the aid had no impact
on their decision to enroll.
1/2
We also showed the same institution that 50% of the students to whom they didn’t offer merit aid
would have been more likely to enroll if aid had been offered.
Case Study: Optimize Financial Aid Allocation
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“I want to maximize enrollment from out-of-state students with GPA’s above 3.0 from low income households. I’ve got $1 million in financial aid to use. 1) To Whom should I offer
the aid??
2) How much should I give each student?
3) How many students can I expect to enroll with that budget?”
1 2
3
Optimize Merit Aid Dollars for Impact
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An Example of A Big Data Analytics Technology Platform
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Using Big Data Analytics to Impact Retention
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As many as 1 in 3 first-year students won’t make it back for sophomore year. The reasons run the gamut from family problems and loneliness to academic struggles and a lack of money.
“ ”
-US News and World Reports
Source: Freshman Retention Rates
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Use Our Tools to Shape Your Class With Students Who Are More Likely To Persist
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An institution’s success is not just about enrollment,
it is about enrolling people who are going to stay
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THANK YOU