Using Big Data in Elections

Using Big Data in Elections

In recent election seasons, campaigns are investing big in a relatively new department: the analytics team. And the 2020 election is no different; in fact, it is perhaps more important than ever before. Now, campaigns can use massive datasets to “micro-target small but influential groups of voters”, and give them an advantage to secure their votes [1]. With more advanced analytics tools, increasing data sources, and abundant variety of consumer information, big data analytics in political campaigns can lead to breakthroughs used to secure victories.

Political analytics teams look at a variety of data sources in order to learn as much about voters as possible. Campaigns look at regional data, including municipality, county, and state level data to determine who you are most likely to vote for. In addition, campaigns used advanced methods to mine for niche data at the individual level. Some of the individual level data collected are:

  • Past participation
  • Historic voting patterns
  • Demographics
  • Psychographics
  • Donation history
  • Political volunteering

Using these data, campaign are then able to effectively segment voters into groups and target them with digital and print media (such as local newspapers) ads and encourage them to vote for a particular candidate. Much of the segmentation is done using advanced algorithms by the analytics team, who then relay the information to the marketing team so they can target ads to them. For example, voters in the Southwest are most likely concerned about immigration policy, so campaigns are more likely to target them with ads about immigration.

However, big data analytics can go awry or have ethical implications. When looking at political data, it can be easy to identify and then ignore those voters who are least likely to vote for you in an attempt to save money. Hillary Clinton’s 2016 presidential campaign did just that. The campaign largely excluded voters who were likely to vote for Trump from political ads and marketing, and thus were no longer attempting to change their minds or persuade them with Clinton’s policies [2].

In addition, ethical implications arise when campaigns micro-target individuals using their personal data. Privacy is a huge concern for individuals who might not want their data to be compromised by campaigns. Analytics teams must also ensure that the data is kept secure, so third parties (such as PACs or private organizations) cannot access the data and use it for their own needs.