The document discusses how the integration of artificial intelligence (AI) and advanced analytics can improve recruitment effectiveness in higher education, particularly at Texas Tech University. It highlights the importance of understanding individual student needs to optimize recruitment strategies and enhance enrollment outcomes. Key takeaways include the necessity of focusing on impactful questions, investing in quality data, and empowering teams to leverage analytics effectively.

1. The Power of Science + Art
How Advanced Analytics Innovations and Staff Empowerment
Can Increase Your Recruiting Effectiveness
Jamie Hansard, Texas Tech
David Babst, Othot
July 16, 2019

2. #TargetXSummit
Agenda
• Introduction
• The Science: How AI is Changing the Game
• Art Meets Science: Using Analytics for Recruitment + Admissions
• Key Takeaways + Concluding Remarks
• Q&A

3. The Science
How Artificial Intelligence (AI) is
Changing the Game

4. What is AI?
https://www.youtube.co
m/watch?v=V1eYniJ0R
nk&vl=en
Sensing an environment and using
data to predict an outcome and then
optimizing the desired result

5. The Heart of AI: Predictions and PrescriptionsVALUE
D I F F I C U LT Y
DESCRIPTIVE
ANALYTICS
DIAGNOSTIC
ANALYTICS
PREDICTIVE
ANALYTICS
PRESCRIPTIVE
ANALYTICS
Hindsight
Foresight
How can we
make it happen?
What will happen?
Why did it happen?
What happened?

6. AI will eventually disrupt and
transform every industry …
… but currently, AI initiatives often only
result in 10% of expected Value
Most organizations have an AI-Value gap

7. Why the AI-Value Gap?
A “Data First” Mentality Enables Modeling
but Fails to Deliver Value
L O W VA L U E
Insular Modeling
(not community-
informed)
Answering
the wrong
question
Data quality
issues
Focused on
data first &
not the
question
Little to no
focus on
deployment
Unsophisticated
feature & variable
engineering

8. H I G H
VA L U E
Engineer Data
and Features
(the right data)
Generate
Community
Knowledge-
Based Models
Deliver Answers
& Actions that
Anyone Can Use
Nail the HIQ
(High Impact
Question)
Focusing on the Question
Delivers Value
H I G H V A L U E

9. A Decision-Making Model
Based on Human Judgment
A Decision-Making Model
That Utilizes AI
A Decision-Making Model
That Combines the Power of AI
+ Human Judgment
Source: Eric Colson, Harvard Business Review, What AI-Driven Decision Making Looks Like
Focusing on Adjusting the
Decision-Making Model
H I G H V A L U E

10. Organizations that figure out the AI-Value Gap win
AI allows us to understand the individual like never before

11. Higher Education and AI
for the Student Life Cycle

12. Higher Education is an industry
facing significant challenges
• Fewer students
• Shifting demographics
• Increased competition
• Pressure on NTR
• Focus on outcomes

13. And today’s students
expect a different
experience
Personalization
Not Generalization
Pathways with Outcomes
Not Promises + Visions
Customized Experiences
Not Standardization

14. OBJECTIVE: Optimize the relationship between the individual and institution
FIT
Academically
Financially
Experientially
PERSONALIZED
EDUCATION
UNIQUE
EXPERIENCE
PERSONAL
DEFINITION of
SUCCESS
LIFELONG
LEARNING
TIME, TREASURE,
TALENTMANAGEABLE DEBT
ENROLLMENT RETENTION/
GRADUATION
POST-
GRADUATE
SUCCESS
ALUMNI
ENGAGEMENT

15. The Othot Difference
UNDERSTAND
THE INDIVIDUAL
CHANGE THE
OUTCOME
EXPLAINABLECONTINUOUS
INTELLIGENCE

16. 1. Focus on individuals
2. Trigger engagement
3. Right tactic at right time
+3% Conversion = $4M per year impact on NTR
Likelihood Scores & Prescriptive Actions Drive Outcomes

17. How do we increase conversion of targeted group of students?

18. Understand What Matters to Your Student
This is what explainable AI looks like

19. Knowing the individual allows you to change the outcome
• Mail a Viewbook
• Meet with a Field Counselor
• Digital Marketing
• Campus Visit
• Financial Aid Offer

20. Knowing the individual allows you to change the outcome
• Mail a Viewbook
• Meet with a Field Counselor
• Digital Marketing
• Campus Visit
• Financial Aid Offer

21. AI Can Change the Outcome
Institutions investing in new approaches:

22. Art Meets Science
Using Analytics for
Recruitment + Admissions at
Texas Tech University

23. Recruitment Challenges at TTU
Funnel
Volume
Adjustment of
Priorities & Goals
Location Resources

24. Evolution of Data + Analytics

25. Leveraging Data + Analytics
Campus-wide
Strategy
Student
Telecounseling
Empowerment of
Admissions Staff
Marketing
Segmentation

26. Records + Results
Reduction of
Search Names
Calling Campaign
Outcomes
Increased
Conversion Rates
Event Attendee
Enhancements
Record
Enrollment
Net Tuition
Increase

27. What’s Next
1. Build and Refine: Recruitment + Marketing
2. Define: Geographic Segmentation
3. Optimize: Financial Aid +
Recruitment/Marketing
4. Expand + Test:
Regional Teaching Sites

28. Science + Art
Key Takeaways, Learnings +
Concluding Remarks

29. Key Takeaways + Learnings
1. Know what questions you need better answers for
from your data.
2. Invest in foundational data and in your own education.
3. Develop a sense for where advancements in analytics
can help you in the coming cycle (and beyond).
4. Signal that this is important and show confidence by
empowering your team and your partners.
5. Test, Measure + Learn. Rinse. Repeat

30. Thank You
Dave Babst: dmbabst@othot.com
Jamie Hansard: Jamie.Hansard@ttu.edu

31. 31OTHOT 31CONFIDENTIAL
Representative List of Partner Schools

32. #TargetXSummit
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33. #TargetXSummit
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