how to increase the value of data captured by admissions
TRANSCRIPT
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July 2017
How to Increase the Value of
Data Captured by Admissions
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Before We Begin
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We are monitoring the discussion and will try to bring the
comments and questions into the conversation.
We are recording the webinar; the webinar archive and slides
will be provided after the event via email.
Join the conversation on Twitter: @CollegisEdu
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About Collegis Education
A strategic operational partner.
Collegis Education is a strategic partner for institutions that face barriers
to long-term success. Guided by our deep-rooted experience in higher
education, our distinctive combination of marketing, technology and
content expertise helps us craft holistic, institutionally aware solutions
that help optimize and expand your reach. We do it all while preserving
what matters most — the heart of your institutional mission and
academic identity.
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Our presenter
4
Jason MeekDirector of AnalyticsCollegis Education
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Agenda
Intro
Presentation
Q & A
Six Takeaways Summary
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Topics
Barriers to Using Data
Types of Student Data
Quality or Quantity
Data Standardization
Benefits of Good Data
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Barriers
Data is everywhere
Not usable
Not connected
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Marketing Systems
More systems
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Enrollment Phases
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Data Sources by Phase
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What Data Can I Collect?
Areas where data can assist in your process:
Awareness stage
Consideration stage
Yield stage
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What Data Can I Collect?
Awareness stage
Website visits
In/outbound phone calls
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What Data Can I Collect?
Consideration stage
Website analytics
Student inquiry form
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What Data Can I Collect?
Yield stage
Student/customer relationship management tool (CRM)
Student information system (SIS)
Learning management system (LMS)
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Use Your Data
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Two Types of Data
1. Manually entered data
2. Behavior based data
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It’s All In the Set Up
The better the data is set up, the easier it is to find insights.
Consider the data’s volume and complexity.
Don’t leave your ability to find insights in the hands of only
your data miners.
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Tips By Type - Student
Manually entered data
Example: student inquiry form
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Sample Inquiry Forms
Basic form
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Sample Inquiry Forms
Advanced
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Student Data
Manually entered data
Collect only what’s necessary
Quantity vs. Quality
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Every piece of data you require/display
on the inquiry form will negatively
effect your form conversion rate.
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Sample Inquiry Form (long)
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Quantity or Quality
You cannot have both.
Which does your institution focus on?
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Quantity or Quality
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Quantity or Quality
How to choose?
Confidence in your admissions team to convert inquiries
into starts
Student mindset
Does your institution typically get students that are
“shopping around?”
Or, the alternate?
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Quantity or Quality
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Quantity:
You may prefer to have more
at the top of your funnel,
regardless of the students’
interest.
Quality:
More prepared for initial
conversations
Greater ability to nurture through
marketing automation
Students willing to provide more
info upfront may already be more
serious about your school.
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Quantity or Quality
Also consider:
Advisor/rep to inquiry ratio
Speed to inquiry requirements
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Data Standardization
Standardize the data as much as possible
Push for structured vs. non-structured (open text)
Drop downs
Check boxes
Radio buttons
Dynamic > Non-dynamic
Example: programs list tied to department header
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See the Difference?
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Advanced Forms
Do you need the same information from all students?
Or, does the data you need vary by degree/school/applicant
type?
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If what you need to collect
changes based on the student,
then vary your forms.
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Tips By Type - College
Manually entered data
Example: CRM/SIS
Standardize the data as much as possible
Audit what is required
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Advisor/Rep Form
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Tips By Type - College
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Standardize the data as much as possible
Drop downs
Check boxes
Radio buttons
Dates
(Inquiry creation, application, deposits)
Interactions
(Phone calls placed, emails sent/replied, etc.)
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Tips By Type
Audit what is required
Data is either “must-have” or “nice-to-have.”
Cut out data that you have proven is not useful to your
enrollment process, or is not predictive to driving a goal.
Don’t just collect data to have data.
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Tips by Type
Test
Write down your assumptions
Let data prove you right
Come up with new theories on what may be drivers for
your prospective students
Change your data entry points
Repeat
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Tips for CRM/SIS Data
Impactful field
Last contact
Drive time/distance to campus
Transfer credits
Event-based data (attendance, grades, etc.)
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Tips By Type - Behavior
Site experience (web analytics tool)
Engagement metrics
Marketing automation data
Chat/instant messaging
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Tips by Type - Behavior
Site experience (web analytics tool)
Compile what pages each student views on your
website(s)
Determine top-influencing pages
Roll the data up by various site areas (ex: financial aid)
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Tips by Type - Behavior
Engagement metrics
Average page depth
Days since last visit
Visit frequency
Visits before conversion
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Tips by Type - Behavior
Sample Engagement Reports
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Tips By Type - Behavior
CRM/SIS
Push the compiled web data into your CRM/SIS systems
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Tips By Type - Behavior
Marketing automation data
Track what is being sent/opened/clicked
Develop strategies to re-engage your students based
on how they are reacting
Use what is being collected from the website to drive
your nurturing campaigns
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Tips By Type - Behavior
Chat/instant messages
Capture date, nature of message
Positive/negative sentiment can be a great indicator. The
most recent interaction is usually the most predictive.
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Grow Your Funnel
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Advanced Tips
“You’re only as good as your word (data)”
Invest in your data
Data quality checks
Data stewards
Create snapshots
Migration of data when changing systems
Democratize insights you do find
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Benefits of Having Good Data
Basics
Accurate reporting
Track what you are doing better
Insights for decision making
Understand what changes should be made
Complex
Combining data silos
Track students through your entire process
Predictive analytics
Use your data to help predict what your students will do
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Questions?
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6 Takeaways
1. Avoid asking for manually entered data
2. Standardize your data
3. Incorporate your behavior-based data
4. Write down your assumptions. Let data prove you right.
5. Test
6. Democratize your data
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Thank You.
CollegisEducation.com