How to Increase the Value of Data Captured by Admissions

July 2017

How to Increase the Value of

Data Captured by Admissions

Before We Begin

We are using WebEx. Please enter questions in the Q&A box.

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

2Copyright Collegis, LLC - Proprietary and Confidential

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.

3Copyright Collegis, LLC – Proprietary and Confidential

Our presenter

4

Jason MeekDirector of AnalyticsCollegis Education

Agenda

Intro

Presentation

Q & A

Six Takeaways Summary


Topics

Barriers to Using Data

Types of Student Data

Quality or Quantity

Data Standardization

Benefits of Good Data


Barriers

Data is everywhere

Not usable

Not connected


Marketing Systems

More systems


Enrollment Phases


Data Sources by Phase


What Data Can I Collect?

Areas where data can assist in your process:

Awareness stage

Consideration stage

Yield stage



Awareness stage

Website visits

In/outbound phone calls



Consideration stage

Website analytics

Student inquiry form



Yield stage

Student/customer relationship management tool (CRM)

Student information system (SIS)

Learning management system (LMS)


Use Your Data


Two Types of Data

1. Manually entered data

2. Behavior based data


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.


Tips By Type - Student

Manually entered data

Example: student inquiry form


Sample Inquiry Forms

Basic form


Sample Inquiry Forms

Advanced


Student Data


Collect only what’s necessary

Quantity vs. Quality


Every piece of data you require/display

on the inquiry form will negatively

effect your form conversion rate.


Sample Inquiry Form (long)


Quantity or Quality

You cannot have both.

Which does your institution focus on?


Quantity or Quality


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?


Quantity or Quality


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.

Quantity or Quality

Also consider:

Advisor/rep to inquiry ratio

Speed to inquiry requirements


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


See the Difference?


Advanced Forms

Do you need the same information from all students?

Or, does the data you need vary by degree/school/applicant

type?


If what you need to collect

changes based on the student,

then vary your forms.

Tips By Type - College


Example: CRM/SIS


Audit what is required


Advisor/Rep Form


Tips By Type - College



Drop downs

Check boxes

Radio buttons

Dates

(Inquiry creation, application, deposits)

Interactions

(Phone calls placed, emails sent/replied, etc.)

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.


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


Tips for CRM/SIS Data

Impactful field

Last contact

Drive time/distance to campus

Transfer credits

Event-based data (attendance, grades, etc.)


Tips By Type - Behavior

Site experience (web analytics tool)

Engagement metrics

Marketing automation data

Chat/instant messaging


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)



Engagement metrics

Average page depth

Days since last visit

Visit frequency

Visits before conversion



Sample Engagement Reports



CRM/SIS

Push the compiled web data into your CRM/SIS systems



Marketing automation data

Email

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



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.


Grow Your Funnel


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


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


Questions?

Copyright Collegis, LLC - Proprietary and Confidential 48

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


Thank You.

CollegisEducation.com

How to Increase the Value of Data Captured by Admissions

Data & Analytics