In this section, we’ll share how your campaign should be using the voter file to learn campaign info. Check out additional Campaign Helpdesk guides on what is the voter file and how to access, if you missed out.

There are two primary ways campaigns categorize voters they would like to contact. You’ll often hear these voters referred to as “universes.”

  1. A persuasion universe includes people who vote regularly, but usually choose to support moderates. As the name suggests, these are the people you believe you can persuade to vote for you.
  2. A get out the vote (GOTV) universe is the flip side of the persuasion universe. These are the people you are confident will vote for you, but also vote inconsistently and could use a motivational push.

People are bucketed into these groups using three main scores determined by predictive modeling:

  • Support score: Using a small citizen groups’ response to candidates and issues, support scores predict who registered voters will support and this data becomes the foundation for developing models.
  • Turnout score: Turnout scores are probabilities on a scale of 0-100, measured from least likely to show up to vote in a general election to most likely.
  • Persuasion model score: Added on occasion, the persuasion score uses the data from support and turnout scores to determine which voters, considered independent or undecided, could benefit from persuading using their model.

These scores are calculated using a good number of variables:

  • Demographics
  • Primaries and elections in which they voted
  • Information from voter registration forms and hundreds of others from commercial and public sources such as the census

What are models?

Support scores usually range from 1-100 and measure whether or not someone supports your candidate or issue.

For your persuasion universe, you’re looking for voters with support scores around 30-70. Because predictive modeling is a guess based around a voter, a score of 50 could mean one of two things - either the voter really is an undecided/moderate voter, or we don’t know much about the voter.

Collecting information from those middle scorers in the field and incorporating it into the modeling allows us to update the uncertain support scores. If you don’t have access to a support score for the specific candidate or issue you’re working on, you can use a Partisanship or Ideology score as a proxy. These models are designed to find people who identify as Democrat/Republican or Progressive/Conservative.

Turnout scores usually range from 0-100. Most people don’t believe it’s worthwhile to reach out to someone with a turnout score below 10 or 20; they choose turnout scores in the middle. Depending on your goals, you may also want to remove people with the highest turnout scores who will likely vote on their own. If you’re doing volunteer recruitment or another activity where you need highly motivated folks, then keep those high turnout score people in your universe.

Persuasion scores identify voters likely to shift their positions based on hearing specific campaign messaging. These types of scores are becoming more and more common. These models are typically centered on 0:

  • negative scorers are voters who are likely to react negatively to your message.
  • positive scorers are people who are likely to be persuaded by your message.

Score ranges vary but they’re generally on a scale of -5 to +5, and campaigns generally talk to people with a score of 2+.

What if a voter doesn’t have a score?

In some cases, you might notice that scores are all over the place or null for people you’ve registered to vote. This is to be expected. Models are scored only periodically, so new people often will not have scores. We also are likely to have less information on newly registered individuals, so the model has less information to use when assigning a score.

We still highly recommend that you put these voters and any voters who have registered since the last November general election into your GOTV universe. Newly registered voters often have less information available and no history of voting, so their turnout scores are lower. Given that they recently took action to register to vote and are likely to be included in turnout efforts if they registered with a voter registration organization, they vote at higher rates than their scores indicate. There are a few states that are now doing “automatic voter registration.” It’s too early to have proper data to say for sure, but it’s likely that the turnout of those automatically registered is lower than those who registered themselves.

Remember, there are restrictions for the voter file. They vary by state, so be sure to familiarize yourself with limitations in your area. Here’s a few examples.:

  • The list cannot be used for commercial purposes.
  • Auto-dialers cannot be used for cell phones.
  • Calls to voters cannot be made outside of certain hours (typically 8am to 9pm).
  • Mass text messages cannot be sent unless voters specifically opt in.

Violation of these rules can lead to revocation of your voter file access as well as hefty fines, so please make sure you understand and comply with your state’s restrictions.

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