Campaign Sciences predictive analytics capabilities deck

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Camapign Sciences is the analytics arm of Wilson Perkins Allen Opinion Research. This deck is our attempt to explain what we do, how we do it and how our clients use it.

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Campaign Sciences predictive analytics capabilities deck

  1. 1. CAMPAIGN SCIENCES 202.470.6300 Analytics for Modern Campaigns
  2. 2. Data, Analytics and the Future of Political Campaigns The last two Presidential Elections showed that political campaigns can no longer rely on traditional strategies if they want to win. •  The Obama Campaign utilized analytics techniques that identified each voter that the campaign could turn out on Election Day •  Rather than solely relying on traditional techniques, Obama’s team based the entire campaign on analysis of voter behavior and ability to predict possible outcomes •  Democratic campaigns across the nation are now building models just like the Obama campaign meaning that, to win, Republicans must be ahead of the curve and preparing our own models •  Campaign Sciences not only has the experience of utilizing predictive analytics successfully for candidates like Senator Ted Cruz but are deploying new methods, staying ahead of the Democrats CAMPAIGN SCIENCES 202.470.6300
  3. 3. What does predictive analytics accomplish? Predictive analytics allows us to make educated predictions about the behavior of individual voters If we can measure a behavior for some voters, we can predict it for all voters: •  Likelihood to Vote •  Candidate preference •  Candidate preference if they vote for non-voters •  Response to a message •  Volunteering •  Donations •  Advocacy CAMPAIGN SCIENCES 202.470.6300
  4. 4. How do we make this happen? We create predictive models based on voter information and firsthand observations •  We collect primary data on planned or observed behavior based on paid calls, volunteer calls, or other campaign sources •  We start with all available information about the voters that you want to understand •  We then narrow down the available variables to only those that are useful predictors of voting habits We start with 200+ variables •  All available aspects of possible voters are included for analysis •  Examples include demographic information such as location, age and gender and behavioral information such as hobbies and interests, and consumer habits CAMPAIGN SCIENCES 202.470.6300
  5. 5. The Variables All of the variables that we use in our models are necessary starting points •  They give us the ability to identify the model that best predicts voter behavior •  It allows us to accurately predict the behavior of other voters who share similar characteristics CAMPAIGN SCIENCES 202.470.6300
  6. 6. What does the data mean? The data that the campaign receives is prediction of each voter’s behavior •  Every voter on the file is given a score from zero to one hundred that records how likely they are to perform any particular behavior •  The higher the value of the score, the more likely the voter performs each behavior CAMPAIGN SCIENCES 202.470.6300
  7. 7. Creating a Winning Team with the Data This data is does more than just predict habits – it helps a campaign identify other key aspects of a winning effort •  Door to Door Walkers: Allows you to focus on “persuadable” voters identified by the model who had larger movements toward the candidate after learning more about them and educate voters on the candidate or ensure that supporters are turned out •  Fundraisers: You won’t have to convince them why the candidate is the right candidate – you can focus on why and how their donations will help (re)elect the candidate •  Ad Buyers: Understand the demographic makeup of “persuadable” voters more acutely and target media buys •  Individual level data can be aggregated back to a population (e.g., DMA) to help identify the best “groups” of voters to target CAMPAIGN SCIENCES 202.470.6300
  8. 8. Going beyond voting habits Analysis of the data can help predict any type of behavior that the campaign wants to understand •  Donations: Based on who has already donated to the campaign, target others likely to donate •  Volunteers: Based on who is already volunteering, target others that could be recruited to volunteer •  Yard Signs: Based on who has requested a yard sign, target others most likely to display a sign •  Events: Based on who has attended previous campaign events, target those most likely to attend future events •  Know before they arrive which are also likely donors or volunteers CAMPAIGN SCIENCES 202.470.6300
  9. 9. Our relationship with the campaign We make it as simple as possible for a campaign to use and implement our data •  The campaign sends us all data they gather or purchase for behaviors they are interested in modeling •  We will clean the data and add all of the demographic, behavior, and consumer information obtained from Aristotle •  We will run our models to predict the behavior •  After predictions are complete we send the scored data (in desired list format) back to the campaign along with Voter ID number to upload back to campaign system (or even handle the upload directly to an accessible database) CAMPAIGN SCIENCES 202.470.6300
  10. 10. Contact Bryon Allen President Bryon@CampaignSciences.org 202.470.6300 CAMPAIGN SCIENCES 202.470.6300

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