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GSAM Perspectives

The Political Gets Analytical


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The Rise of Big Data in Elections

Big data has become a powerful tool for the modern political candidate. Complex models allow campaigns to gain a much more refined understanding of constituents at the individual voter or household level, whereas prior campaigns were typically limited to the general demographics of the state, county or zip code.

Micro-targeting of voters through the use of data analytics gained momentum in the 2008 and 2012 election cycles. David Plouffe, Barack Obama’s 2008 presidential campaign manager, noted that, “In both Obama campaigns, we had outsized advantages over our opponents, both in the quality of our data analytics and predictive modeling, as well as our belief in it. It’s how we made every decision.” Similarly, Obama’s 2012 re-election campaign manager Jim Messina made a pledge to “measure every single thing” in the campaign. That pledge resulted in the formation of a dedicated team of over 100 data analysts focused entirely on collecting vast amounts of data on campaign operations and the electorate. A new frontier of campaign analytics was born. Reflecting on the use of real-time metrics, Messina commented that, “Every night for 18 months, we did 66,000 computer simulations of the election, and that’s how we based our tactics—we based it all on big data.”1

Since the 2012 election cycle, the amount of time Americans spend watching television has decreased, while the amount of time they spend online has almost doubled.2 Traceable online activity – people’s digital footprint – reveals data about each voter’s individual preferences and behaviors, and campaigns are able to use this information to better understand and communicate with their target constituents.

This tactic was featured in the Netflix series House of Cards, when Frank Underwood, fictional US president, grows increasingly alarmed by his opponent’s use of big data analytics to sway public opinion in the series’ fourth season. By leveraging big data, candidates can effectively segment the voter population across a variety of metrics, including basic demographics (such as income and gender), lifestyle data and historical tendency to vote for a certain party. Candidates can also mine data from social media and other websites to measure individual voter interests, associations and affiliations. Once candidates have gained a clearer picture of their voters’ identities, they can then adapt their communication strategy accordingly with the goal of more effectively reaching their target (and most receptive) audience. Rather than pursue mass mailings or call campaigns, candidates can focus their efforts on voters that could make the biggest impact on election day. Strong supporters can be identified early on and enlisted as local influencers or canvassers in the field, and potential swing voters can be prioritized in outreach campaigns—the goal to micro-target each individual voter, in mass scale, across the entire nation.

Understanding a campaign’s voter base can also influence the medium that candidates use to communicate their message. For example, television ads are a common marketing tactic, but research has shown that one-third of voters do not watch live TV each week, while 52% of voters watch online videos on a weekly basis. By using big data to understand the behaviors and preferences of target voters, candidates can deliver content on the platforms that voters are most likely to use, thereby more efficiently using campaign resources and also potentially bringing down per voter acquisition costs.

Bernie Sanders implemented this strategy ahead of the 2016 Iowa caucuses when he launched a massive social media advertising campaign targeted at millennials. The ad campaign stretched twelve days and reached a wide mass of people on Facebook and Instagram in Iowa, 85% of whom were in the millennial age group.3 By focusing his efforts on a platform that millennials use frequently, Sanders was able to reach a large portion of his target audience in a remarkably short span of time.

Big data can help candidates determine the delivery strategy for their communications, and also shape the content of the communications themselves. Candidates can address the same issue in different ways to appeal to different audiences depending on their preferences and beliefs. By personalizing the content of its outreach emails in the 2012 election, Obama’s campaign was able to fundraise $460 million from email donations, whereas Mitt Romney’s email outreach efforts only garnered $130 million. Matt Rhoades, former campaign manager for Romney, shared “Unfortunately, it took Governor Romney's loss in 2012 for Republicans to get serious about funding our party’s data programs.” Candidates may also deliver personalized content through voter-targeted digital advertising services. These services use voter registration data to identify individuals by voting history or party affiliation and then serve them customized ad content that addresses specific political issues or positions that are of interest to the voter. The ability to use data to define voter specfic messaging, and then determine how best to deliver the messaging creates a partnership that is difficult to beat.

From analyzing social media and demographic information to targeting and motivating voters, big data has become a powerful force in the election process in the US and increasingly in other countries as well. And while the tools and methods candidates use will continue to evolve, the large-scale interpretation and analysis of data is likely to be a centerpiece of most future political campaigns.

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