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V
TECHNOLOGIES AND TIPS TO
HELP ENROLLMENT MARKETERS
BE MORE EFFECIENT
A Collaboration between Datamark,
Leads360 and C3Metrics
ABOUT LEADS360
• A web-based software-as-a-service company (SaaS) established
in 2004
• Market leader in the B2C prospect management sector in all of
our core verticals – Financial Services (Mortgage, Debt, etc.) and
Insurance and rapidly growing in Education
• The only enrollment management system designed for schools
that compete for students
• Over 5,000 clients ranging from 1 to 1,000+ users
• More than 50 million active records under management
• 1,400 data source integrations
• More than 100 third party technology integrations
ABOUT C3 METRICS
•
The C3 Metrics SaaS platform delivers real-time attribution and viewable
impressions, allowing marketers to abandon last click measurement and
discover the truth
•
Buyers and sellers turn to C3 Metrics because its award-winning platform
and products complete the loop and automate the process of correctly
reporting which viewed media creates awareness, interest, and action
•
C3’s technology is certified by Google Display, Yahoo!, AOL, and runs
on 27+ DSP’s and networks
•
Headquartered in New York with offices in San Diego and Portsmouth, New
Hampshire, C3 Metrics is comprised of leading experts in the field of digital
and TV measurement from DoubleClick, eBay, PepsiCo, Yahoo! and
Nielsen
ABOUT DATAMARK
•
For 25 years, Datamark has provided
innovative, data-driven marketing
exclusively to higher education.
•
We generate high-quality student
prospects for colleges and
universities of all types and sizes
across the country.
•
We offer full-service inquiry
generation and management;
complete with conversion marketing
solutions designed to reach, engage
and motivate prospective students at
every stage of the enrollment process.
“There is no such thing as a mass mind. The
mass audience is made up of individuals, and
good advertising is written always from one
person to another. When it is aimed at
millions it rarely moves anyone.”
— Fairfax Cone
STATE OF THE MARKET
CPLA’s Q1 2013 success seems largely based
on its own superior execution and high quality
product offering. Management reiterated that
market conditions remain weak and credited
gains to improved [enrollment] rates… as a
result of its own strategic and tactical choices.
-Wells Fargo, Analyst Report, 23 April 2013
TECHNOLOGIES AND TIPS
Save time and / or money
Deliver a market or competitive advantage
OPPORTUNITY #1
Find more efficient ways to communicate
with prospective student inquiries.
OPTIMIZE THE ADMISSIONS FUNNEL
• Distribution
o Basics
o Advanced
• Inquiry volume per admissions rep
• Scoring
DISTRIBUTION IS A SIMPLE CONCEPT
 dis·tri·bu·tion
/lēd distrəˈbyo͞oSHən/
 “The act of sharing inquiries among admissions
representatives.”
DISTRIBUTION STRATEGIES
PUSH
PULL/PUSH
ROUND-ROBIN
+
PULL
BLIND QUEUE
ATTRIBUTE-BASED
SHARK TANK
SKILL-BASED
PERFORMANCE-BASED
SHOTGUN
QUALIFY AND TRANSFER
QUAL-CONF-TRANSFER
CHERRY-PICK
SOPHISTICATED DISTRIBUTION METHODS
PUSH
PULL/PUSH
Leads are in buckets
Inquiries handed out
ROUND-ROBIN
+
ATTRIBUTE-BASED
BLIND QUEUE
SHARK TANK
SKILL-BASED
PERFORMANCE-BASED
PULL
SHOTGUN
QUALIFY AND TRANSFER
QUAL-CONF-TRANSFER
CHERRY-PICK
SKILL-BASED DISTRIBUTION
“Play to Each Rep’s Strengths”
BEST FIT INQUIRES TO BEST FIT REPS
Good with
veterans
Good with
working
moms
Good with
Website
inquiries
Good with
inbound
phone calls
HOW SKILL-BASED DISTRIBUTION WORKS
STEP 1
Analyze “skills”
you want to
optimize e.g.
State, Education,
etc.
Choose skills
that cover many
opportunities
and have a high
variance in
performance
among
admissions reps
STEP 2
Analyze which
reps should be
in each “skill
team” by
asking, Who is
comparatively
the best at
each type of
inquiry?
There will be
one group with
no assigned
skill
STEP 3
Set skill-based
distribution to
distribute
preferentially
STEP 4
Analyze results
and refine
SKILL-BASED ROUTING RESULTS
Change in enrollment rate following implementation
of Skill-Based Distribution
PERFORMANCE-BASED
DISTRIBUTION
“Auto-optimizing Your Skill-Based
Distribution”
PERFORMANCE-BASED DISTRIBUTION
What does it do?
Automatically distributes inquiry to the bestsuited admissions rep based on each rep’s:
•Contact rate
•Qualification rate
•Enrollment rate
•Other Milestones
Why is this useful?
- Allows flow of inquiries according to competence
- Does not require continuous analysis and
changing of caps and filters
AS REP’S PERFORMANCE CHANGES…
1
My
Enroll
Rate
Daily
Inquiries
2
4
3
5
6
7
8
4.5%
4.2%
5.5%
7.6%
7.2%
8.3%
8.2%
8.5%
5
4
6
10
10
14
13
14
GETTING INQUIRY VOLUME RIGHT
WORKLOAD IMPACT ON ENROLLMENT
• Enrollment rates decrease as more new inquiries
are assigned per rep
o As workload increases, employees’
effectiveness is also likely to decrease (speed
to call drops)
o As volume increases, inquiry quality is likely
to decrease
• Can discern a formula for relationship between
new leads assigned and enrollment rate
WORKLOAD IMPACT ON ENROLLMENT
50.0%
Enrollment Rate per Rep
45.0%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
5.0%
0.0%
0
5
10
15
New Inquiry Assignments per Rep
20
25
PREDICTING ENROLLMENT RATE
EER = 0.3075*N-0.832
EER = expected
enrollment rate
N = new inquiries
per rep per day
based on guessing
or current stats
New Inquiries per Rep
per Day
1
2
3
4
5
8
10
12
15
20
25
30
Expected Enrollment
Rate
30.8%
17.3%
12.3%
9.7%
8.1%
5.5%
4.5%
3.9%
3.2%
2.5%
2.1%
1.8%
SCORING
SCORING
What does it do?
Allows you to score inquiries according to their:
- Demographic attributes
- Inquiry source
- Level of interest (e.g. email opens)
Why is this useful?
Follow different workflow paths based on
interest:
- Send different emails and text messages
- Distribute to different admissions reps
- Increase priority as new information
changes score
DISAGREEMENT ABOUT INQUIRY QUALITY
Why are you
prioritizing inquiries
that are women?
Because they are the
best-fit inquiries
No, veterans are the
best-fit inquiries
Marketing
Manager
Admissions
Manager
DISAGREEMENT ABOUT INQUIRY QUALITY
OK, let’s sit down
and figure out
what makes a
“best fit” inquiry
Sure, and then we’all
document it as a
scoring system for all
inquiries
Marketing
Manager
Admissions
Manager
SCORING EXAMPLES
•
You want to distribute your best-fit inquiries to your most experienced
admissions reps
•
You want to attempt to call the best-fit inquiries more than others
•
A high quality inquiry is usually one that is a good fit and ready to make a
decision, so your emails should have a more urgent tone with a clear call
to action
•
Prioritization rules should favor a best-fit inquiry over a lower quality
inquiry
•
You have an agreement with your PPL provider that you may return your
very worst inquiries
DIFFERENT SCORING MODELS
Rules-based
Model-based
How it works
•
•
You determine what makes a bestfit inquiry and configure rules
Examples:
• Have job = +1
• No GED = -3
• Email open = +4
• Email bounced = -5
• App requested = +10
•
•
Vendor runs models to determine
best rules and then configures
scoring
Each inquiry scored against model
Example vendors
•
•
Leads360
Salesforce
•
•
Neustar
eBureau
Value Brings
•
•
Easy to set up
Model visibility
•
•
More complex
Can be included as a factor in
determining score
OPPORTUNITY #2
Determine the overall impact of
each marketing channel.
ATTRIBUTION
MULTIPLE DIGITAL MEDIA CHANNELS
Google
Bing/Yahoo
Ad Networks
CPL
Social
HOW ‘CLICK’ TRACKING WORKS
Google
Bing/Yahoo
CPL
Cookie
‘click-thru’
HOW ‘VIEW’ TRACKING WORKS
Cookie Dropped
Social
Ad Networks
Cookie
‘view-thru’
Cookie Dropped
THANK YOU / CONFIRMATION PAGE
ValueClick (Ad
Network)
DoubleClick (Ad
Network)
CPA Affiliate (CPA)
Google (Search)
Trialpay (CPA)
SAME DAY INQUIRY
GOOGLE
‘CLICK-THRU’
COOKIE
Prospective student searches for
‘online degree’
and clicks on Google paid search
Lets look at the code
SAME DAY INQUIRY
DoubleClick (Ad
Network)
CPA Affiliate (CPA)
Google Cookie Finds a Match & ‘Fires’
Google (Search)
Trialpay (CPA)
Facebook (Social)
PATH TO INQUIRY IS NEVER THAT DIRECT
Prospective Students Take Multiple Days via Multiple Channels
MULTI-DAY AND MULT-CHANNEL INQUIRIES
RESULT IN CONFUSION
1. Data from ad networks not adding up
2. Data from search PPC not adding up
3. Data from CPL not adding up
4. Bad data results in bad decisions
A BEST KEPT SECRET OF DIGITAL MARKETING
“One of the best-kept secrets in
online marketing is that most
campaign attribution data is
completely wrong and the
models used to evaluate
campaign performance are
wholly inappropriate.”
Published April 2009
“Hundreds of millions of dollars are wasted annually on
marketing efforts that don’t produce their intended results.”
TYPICAL SCENARIO
DAY 1:
Visitor views ad
on Facebook
DAY 2:
Visitor search for
Social
Non-Brand Paid Search
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
Visitor search for
‘university of …’
Ad Network
Brand Paid Search
Conversion
ALL COOKIES FIND A MATCH
Ad Network Finds a Match & ‘Fires’
DoubleClick (Ad
Network)
CPA Affiliate (CPA)
Google Cookie Finds a Match & ‘Fires’
Google (Search)
Trialpay (CPA)
Social / FB Finds a Match & ‘Fires’
Facebook (Social)
EVERY PARTNER TAKES CREDIT
One Enrollment = 3 Claiming Credit
Each Partner Sees Their Pixel Firing & Claims Credit
ANALYTICS POINT IN THE WRONG DIRECTION
+
Analytics: Brand Search Term ‘university of ..’ led to inquiry
Response: Increase Brand PPC Spend, Cut Network, Non-Brand Search & Social
Result: Smaller Funnel & Less Conversions
What’s Happening Down Below?
AD NOT SEEN
Yes – Cookie Dropped
68%
Digital Ads Not Seen
AD NOT SEEN JUMPS INTO LAST PLACE & WINS
DAY 1:
Visitor views ad
on Facebook
DAY 2:
Visitor search for
Social
Non-Brand Paid Search
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
Visitor search for
Ad Network
Brand Paid Search
‘university of …’
DAY 22:
Visitor cookied by
Ad not seen
Ad Not Seen
Conversion
AD NOT SEEN JUMPS INTO LAST PLACE & WINS
DAY 1:
Visitor views ad
on Facebook
DAY 2:
Visitor search for
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
Visitor search for
‘university of …’
DAY 22:
Visitor cookied by
Ad not seen
✗
✗
✗
NO
CREDIT
No Credit for
Origination or
Assisting the
Conversion
100%
Credit
Conversion
HERE’S THE ACTUAL COST
1,000 Conversions
X
68%
not seen
$30 CPI
‘actual’ CPI = $94
$30,000 / month
Only pay for Viewable Conversions (Cost $9,600)
Save $20,400 / month
STEP 1: CAPTURE EVERY MEDIA TOUCH POINT
DAY 1:
Originator
Visitor views ad
on Facebook
DAY 2:
Roster
Visitor search for
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
Visitor search for
Roster
Assist
‘university of …’
DAY 22:
Visitor cookied by
Ad not seen
Converter
Conversion
STEP 2: SKIP OVER ADS NOT SEEN
DAY 1:
Visitor views ad
on Facebook
DAY 2:
Roster
Visitor search for
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
Visitor search for
Assist
Converter
Conversion
‘university of …’
DAY 22:
SKIP OVER ADS NOT SEEN
Visitor cookied by
Ad not seen
BRAND SEARCH CONVERSION CONTROLS
Last step in conversion is
user navigating to the
site
Majority of prospective
students navigate via
brand search, SEO or
direct website visit
STEP 3: SKIP LAST CLICKED BRANDED SEARCH
DAY 1:
Visitor views ad
on Facebook
Assist
DAY 2:
Visitor search for
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
Converter
Conversion
SKIP BRAND SEARCH
SKIP OVER ADS NOT SEEN
Visitor search for
‘university of …’
DAY 22:
Visitor cookied by
Ad not seen
NEW LENS FOR ROI: ACPI
Attributed Cost Per Inquiry
SPLIT VALUE BASED ON THE DATA
DAY 1:
Visitor views ad
on Facebook
Assist
DAY 2:
Visitor search for
20%
‘online degrees’
DAY 15:
Visitor clicks on
Network Banner
DAY 22:
40%
Converter
Conversion
SKIP BRAND SEARCH
SKIP OVER ADS NOT SEEN
Visitor search for
‘university of …’
DAY 22:
Visitor cookied by
Ad not seen
ATTRIBUTE EVERY INQUIRY BY EVERY TOUCH
POINT
3,000 Conversions where ‘online degree’ was the assist
Assist
600
3,000
Attribution Model
Attributed Leads
(Example 20% Model shown)
(3000 X Assist %)
IMPORT MEDIA COSTS AND CALCULATE CPI
Calculate Ratio of Attributed Orders vs. Cost
2500
2000
2000
1500
Attributed Leads
1000
Media Spend
500
600
0
2,000/600 = 3.33 ACPI
CPL RESULTS DISPLAYED IN THE DASHBOARD
TECHNOLOGIES AND TIPS
Save time and / or money
Deliver a market or competitive advantage
EFFICIENCY TIP #1
Move your time
consuming,
small run print
jobs to an
online store
front.
BENEFITS OF AN ONLINE STORE
• Fast:
Order 24/7/365
• Customizable:
Edit creative whenever necessary
• On-demand:
Print what you want when you want
• Simple:
Access everything in one place
• Competitive:
Pay competitive rates
EFFICIENCY TIP #2
A communication audit
of all outbound
messaging will likely
reveal some
communication issues.
MONROE COMMUNITY COLLEGE
286
=
Messages About
Early Enrollment
60%
30%
10%
AFTER THE AUDIT
30%
50%
Early Enrollment
Appointments for
Placement Exams
EFFICIENCY TIP #3
Aggressively update your business rules.
If…
…Then
TWO EXAMPLES
Fulfillment:
Immediate vs. 48 hours?
Faster push to closed status
(also see Efficiency Tip #4)
EFFICIENCY TIP #4
HOUSE FILE
Your house file
of unconverted
inquiries is
likely a highly
untapped
resource.
$
RE-ENGAGE REGULARLY
MONTHLY:
NEW TO FILE AND
TOP TIER NAMES
REGULARLY:
OTHER TOP
TIER NAMES
OCCASIONALLY:
MID TIER AND
OLDER NAMES
Thank you.

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