Magellan Strategies Colorado Voter Segmentation Overview 052114

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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.

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Magellan Strategies Colorado Voter Segmentation Overview 052114

  1. 1. Going Beyond the Voter File: Using Predictive Data Modeling to Dramatically Improve Voter Targeting 2
  2. 2. 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. 3
  3. 3. How do most campaign decision makers use voter file data to target voters for turnout and persuasion programs? 4
  4. 4. 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 5
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  6. 6. 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. 7
  7. 7. How can predictive data modeling improve our voter targeting in Colorado? 8
  8. 8. 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. 9
  9. 9. 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. 10
  10. 10. 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
  11. 11. 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
  12. 12. What is the Colorado Voter Segmentation Project? 13
  13. 13. Colorado Voter Segmentation Project 14 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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  19. 19. How was it done? 20
  20. 20. 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. 21
  21. 21. 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.” 22
  22. 22. 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.” 23
  23. 23. 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.” 24
  24. 24. 25 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.
  25. 25. How can the data be used? 26
  26. 26. 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. 27
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  28. 28. 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. 29
  29. 29. Thank you for your time today! 30
  30. 30. 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 31

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