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The Role of Innovation and Evidence-Based Decision Making
in the 2016 U.S. Election 1
Background
When Reality TV became Reality
2
•Fake News
•Global rise of
Nationalism/Populism
•Obama Backlash
•Rapidly changing media
and tech landscape
•Xenophobia/Racism
•Shifting national
demographics
•The Russians!
•Decline of Legacy
Institutions
•Economic uncertainty
•Weak Republican
opponents
•Echo Chambers
3
•Lack of Hillary appeal
•Anti-Establishment
sentiment
•Bots
•Sensationalist, gossipy
news coverage
•Media’s need for
ratings/subscriptions
•We’re going to vote
Republican no matter what
•The “Make America Great
Again” Brand
•WikiLeaks
•James Comey
•Low voter turnout
•Use and Misuse of Data
Science
Notable Factors
CLASS Themes
Which was Hillary’s biggest mistake?
4
Hillary’s Hamartia
• Barak’s voters will vote for me
• Traditional campaigning and media
channels will work as they always have
• The polls have me winning in a landslide
• There is no F@CKING! way any sane
person could possibly vote for this guy
5
Moneyball
Trump’s Innovations and Parallels to the book
6
Take advantage of Market Inefficiencies
7
• The Electoral
College
• Free and
Earned Media
Challenge Conventional Wisdom and Strategy
• Digital and social media first campaign - Faster, more responsive, more efficient,
more in tune with sentiment, more up to date
• Incendiary rhetoric and themes - The world is falling apart!!! Everybody is the bad
guy!!! I can save us!!!!!
• Star power/Freakshow effect - Trust me, I’m a billionaire./”What the hell, nothing
else is working - let’s give it a shot.”
• “I’m just like you” - And Washington isn’t. Let’s drain the swamp.
8
Seek Fresh Perspectives and Employ
Alternative Expertise
9
Alexander Nix
CEO of Cambridge Analytica
Jared Kushner
Director of Operations
Steve Bannon
Chief Strategist
Cambridge
Analytica
The same firm that worked on the Brexit
campaign bring a new methodology for
reaching and persuading voters
10
11
Personality Assessment + Microtargeting = Cambridge Analytica
12
So now what???
13
RNC Data
Own list of
Trump
supporters
External
Data
(Experian,
Datalogix,
Epsilon)
Email Lists
(Newt
Gingrich, Tea
Party)
Cambridge
Analytica
Lookalike
Modeling
Project
Alamo
A/B Testing
• 40,000-50,000 variations of targeted ads per day
• Continuously measure and adapt to responses, by giving instant feedback to their automated AI model
• “Did this swing voter respond to the ad attacking Clinton’s negligence over her email server? Yes? Serve her
more content that emphasizes failures of responsibility. No? The script tries a different headline that
corresponds to another personality trait - like their tendency to be agreeable towards authority figures. For
example, ‘Top Intelligence Officials Agree: Clinton’s emails jeopardized National Security.”
• And the cycle repeats. If an ad repeatedly fails to engage, the system moves on to the next to save resources
14
● Based on responses, the Trump team could see which
messages and issues were resonating and where.
● This info was also used to determine Trump’s rally locations
and important issues. If 73% of targeted voters in a Michigan
county clicked on ad focused on bringing back jobs, they
would schedule a rally close by focused on economic
recovery.
15
Voter Suppression
• Targeted certain voters with a low propensity to vote, who they thought might lean
towards Hillary
• For certain blacks, ads from 1996 featuring Hillary’s “Superpredator” line
• For Haitians in Miami’s Little Haiti neighborhood, ads about the Clinton’s lack of
relief effort after the Haiti earthquake
• For women, ads about Bill Clinton’s philandering and Hillary’s lack of response
16
Phone App
• Flagged certain households that the model showed to be “highly receptive” to Trump’s
messages
• Canvassers could then communicate with these households, based on their given
personality type
• They would update the app, and the data team would know in real time who had been
“reached,” and where to continue their efforts
• This made their GET OUT THE VOTE ground tactics faster and more efficient than Clinton’s;
her canvassing operation was supposedly done on paper
17
Meet our new president!
18
Food for
Thought
The power and danger of data is real. We
better remember what we learned in here, or
we all might suffer the same fate as Hillary.
19

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The Role of Innovation and Evidence-Based Decision Making in the 2016 U.S. Election

  • 1. The Role of Innovation and Evidence-Based Decision Making in the 2016 U.S. Election 1
  • 2. Background When Reality TV became Reality 2
  • 3. •Fake News •Global rise of Nationalism/Populism •Obama Backlash •Rapidly changing media and tech landscape •Xenophobia/Racism •Shifting national demographics •The Russians! •Decline of Legacy Institutions •Economic uncertainty •Weak Republican opponents •Echo Chambers 3 •Lack of Hillary appeal •Anti-Establishment sentiment •Bots •Sensationalist, gossipy news coverage •Media’s need for ratings/subscriptions •We’re going to vote Republican no matter what •The “Make America Great Again” Brand •WikiLeaks •James Comey •Low voter turnout •Use and Misuse of Data Science Notable Factors
  • 4. CLASS Themes Which was Hillary’s biggest mistake? 4
  • 5. Hillary’s Hamartia • Barak’s voters will vote for me • Traditional campaigning and media channels will work as they always have • The polls have me winning in a landslide • There is no F@CKING! way any sane person could possibly vote for this guy 5
  • 6. Moneyball Trump’s Innovations and Parallels to the book 6
  • 7. Take advantage of Market Inefficiencies 7 • The Electoral College • Free and Earned Media
  • 8. Challenge Conventional Wisdom and Strategy • Digital and social media first campaign - Faster, more responsive, more efficient, more in tune with sentiment, more up to date • Incendiary rhetoric and themes - The world is falling apart!!! Everybody is the bad guy!!! I can save us!!!!! • Star power/Freakshow effect - Trust me, I’m a billionaire./”What the hell, nothing else is working - let’s give it a shot.” • “I’m just like you” - And Washington isn’t. Let’s drain the swamp. 8
  • 9. Seek Fresh Perspectives and Employ Alternative Expertise 9 Alexander Nix CEO of Cambridge Analytica Jared Kushner Director of Operations Steve Bannon Chief Strategist
  • 10. Cambridge Analytica The same firm that worked on the Brexit campaign bring a new methodology for reaching and persuading voters 10
  • 11. 11 Personality Assessment + Microtargeting = Cambridge Analytica
  • 12. 12
  • 13. So now what??? 13 RNC Data Own list of Trump supporters External Data (Experian, Datalogix, Epsilon) Email Lists (Newt Gingrich, Tea Party) Cambridge Analytica Lookalike Modeling Project Alamo
  • 14. A/B Testing • 40,000-50,000 variations of targeted ads per day • Continuously measure and adapt to responses, by giving instant feedback to their automated AI model • “Did this swing voter respond to the ad attacking Clinton’s negligence over her email server? Yes? Serve her more content that emphasizes failures of responsibility. No? The script tries a different headline that corresponds to another personality trait - like their tendency to be agreeable towards authority figures. For example, ‘Top Intelligence Officials Agree: Clinton’s emails jeopardized National Security.” • And the cycle repeats. If an ad repeatedly fails to engage, the system moves on to the next to save resources 14
  • 15. ● Based on responses, the Trump team could see which messages and issues were resonating and where. ● This info was also used to determine Trump’s rally locations and important issues. If 73% of targeted voters in a Michigan county clicked on ad focused on bringing back jobs, they would schedule a rally close by focused on economic recovery. 15
  • 16. Voter Suppression • Targeted certain voters with a low propensity to vote, who they thought might lean towards Hillary • For certain blacks, ads from 1996 featuring Hillary’s “Superpredator” line • For Haitians in Miami’s Little Haiti neighborhood, ads about the Clinton’s lack of relief effort after the Haiti earthquake • For women, ads about Bill Clinton’s philandering and Hillary’s lack of response 16
  • 17. Phone App • Flagged certain households that the model showed to be “highly receptive” to Trump’s messages • Canvassers could then communicate with these households, based on their given personality type • They would update the app, and the data team would know in real time who had been “reached,” and where to continue their efforts • This made their GET OUT THE VOTE ground tactics faster and more efficient than Clinton’s; her canvassing operation was supposedly done on paper 17
  • 18. Meet our new president! 18
  • 19. Food for Thought The power and danger of data is real. We better remember what we learned in here, or we all might suffer the same fate as Hillary. 19