This presentation explains a predictive data modeling project that segmented Colorado's 3.5 million voters into 11 groups. The segmentation enables campaign decision makers the ability to understand and target voters beyond data that is is available on a Colorado voter file.

2. Going Beyond the Voter
File:
Using Predictive Data Modeling
to Dramatically Improve Voter
Targeting
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3. Successful campaigns use data and
information to make decisions. Voter file
data is the most common source of data
used by campaigns because it is affordable
and readily available.
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4. How do most campaign
decision makers use
voter file data to target
voters for turnout and
persuasion programs?
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5. Traditional Voter Targeting
Methods Using Voter File Data
 Voted in 4 of the past 4 general elections
 Voted in last two off year elections, 2006
and 2010
 Voters that have never voted in a primary
 Target by party, Republicans and
independents.
 If available, past voter ID work on file,
identifying Romney voter, Obama voter,
etc.
 If available, issue preference data, pro-life,
pro-gun, control government spending
 Social networking or digital data
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7. Limits of Traditional Voter
Targeting Methods Using Voter
File Data
 You can only target by party, age,
gender and vote history, OK for turnout,
not great for persuasion
 You don’t know who the weak
Republicans are, which are open to
voting for a Democrat
 Among independents, you know who is
likely to vote, but you don’t know which
ones lean Republican, which are truly in
the middle, and which ones are
Democrats in disguise.
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8. How can predictive
data modeling
improve our voter
targeting in
Colorado?
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9. What is Predictive Data Modeling?
English Version:
Predictive data modeling predicts a voter’s
political beliefs. It predicts if someone is
pro-life, pro-gun, or pro-gay marriage. It
predicts if you are voting for Cory Gardner
or Mark Udall, or if you are voting for a
Republican candidate or a Democrat
candidate for the state legislature.
It predicts if you are going to vote or not
this November. The ability to predict these
things in an election is a competitive
advantage.
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10. What is Predictive Data Modeling?
Statistical Version:
Predictive data modeling encompasses a
variety of statistical techniques, machine
learning, mathematical algorithms and
data mining to make predictions about
future behavior or future events .
Businesses of all shapes and sizes use
predictive data modeling to run their
operations more efficiently, to make better
decisions, and to gain a competitive edge
over their competitors.
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11. Examples of Predictive Data
Modeling in Business
 LinkedIn and Facebook predict your
friends and colleagues.
 Comcast, DirectTV, and phone carriers
predict “churn”, customers that are
about to switch to a competitor.
 Target famously predicted women
customers that were about to become
pregnant based on purchasing data.
 Amazon predicts suggested sales
purchases effectively.
 Insurance companies predict when you
die. 11

12. Examples of Predictive Data
Modeling in Business
 The IRS uses predictive modeling to
predict individuals hiding income.
 Hewlett Packard human resources
department has a modeling score for
each employee to predict who is likely
to leave the company or quit.
 Medical researchers predict cancer
better than doctors by using patient
data.
 The 2012 Obama campaign used
predictive modeling to create a
superior voter targeting program. 12

13. What is the Colorado
Voter Segmentation
Project?
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14. Colorado Voter Segmentation Project
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It puts all 3.5 million Colorado
voters into 11 segments.
It segments Republican voters
into 4 groups, ranging from very
conservative to moderate in
their political beliefs.
It segments Democrats voters
into 4 groups, ranging from very
liberal to moderate in their
political beliefs.
It segments Independent voters
into 3 groups, Lean Republican,
Lean Democrat and the “True
Middle”.

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20. How was it done?
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21. Colorado Voter Segmentation
Modeling Project, Feb. 2014
 9,500n statewide survey of Colorado
registered voters
 Built 21 different predictive models based
on questions about views of government,
fiscal issues, social issues, domestic
issues.
 Grouped 3.5 million voters into 11
definable and easy to understand
segments.
 Cross referenced with past vote history.
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22. CO Voter Segmentation Survey Questions
“Please tell me if you agree or disagree
with the following statements….”
“Government is almost always wasteful and
inefficient.”
“The government should do more to help
needy Americans even if it means going
deeper into debt.”
“Poor people have it easy because they
can get government benefits without doing
anything in return.”
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23. CO Voter Segmentation Survey Questions
“Please tell me if you agree or disagree
with the following statements….”
“Too much power is concentrated in the
hands of a few large companies.”
“Government regulation of business is
necessary to protect the public interest.”
“Immigrants today are a burden on our
country because they take our jobs,
housing and health care.”
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24. CO Voter Segmentation Survey Questions
“Please tell me if you agree or disagree with the
following statements….”
“Homosexuality should be discouraged by society.”
“Gay and lesbian couples have the right to get
married.”
“Stricter environmental laws and regulations cost
too many jobs and hurt the economy.”
“I have more than enough money to pay my bills
comfortably.”
“The only good reason for anyone to own a gun is
if they are employed by a law enforcement
agency.”
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0%
10%
20%
30%
40%
50%
60%
70%
80%
74%
67%
58%
47%
54%
38%
34% 36%
32%
24%
12%
Hard Republican Solid Republican Soft Republican
Weak Republican Rep Leaning Unaffiliates True Middle
Dem Leaning Unaffiliates Weak Democrat Soft Democrat
Solid Democrat Hard Democrat
COLORADO SEGMENTATION
PROJECTGovernment is almost always wasteful and inefficient.
Percentage that strongly agree.

26. How can the data be
used?
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27. Using the Data to Improve Voter
Targeting
 There are 175,993 independent voters
in the “True Middle” segment that have
voted in 4 of the last 4 general
elections. They are going to vote this
November so they need be surveyed,
understood and communicated with.
 There are 45,674 Solid Republicans
and 60,193 Soft Republicans that voted
in 2 of the last 4 elections. They need to
be turned out to vote.
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29. Using the Data to Improve Voter
Targeting
 There are 62,038 independent voters
that lean Republican and voted in 4 of
the past 4 elections. They should be
surveyed for issue preference and then
turned out to vote.
 There are 34,404 independent voters
that lean Republican and voted in 3 of
the past 4 general elections, they
should be surveyed, put into a voter id
pool and then turned out to vote.
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30. Thank you for your time today!
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31. David Flaherty - CEO
www.MagellanStrategies.com
Dflahery@MagellanStrategies.com
Denver Office
303-861-8585
1685 Boxelder Street, Suite 300
Louisville, CO 80027
Contact Magellan Strategies
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