In the aftermath of last month’s presidential election, the media has increasingly focused on both campaigns’ use of big data technology to track, target, and persuade potential voters. According to Ethan Roeder, Data Director for the Obama campaign, “what’s really new in politics today is not the data itself but how campaigns make sense of it. Cheaper and more plentiful computing power allows campaigns to process far more information than ever before to look for patterns, trends and correlations.” The Obama campaign in particular used a host of strategies to determine likely voters and turn them out on Election Day. No other presidential campaign to date has utilized big data analytics to such a high degree to predict voter behavior. The strategy combined two of the most interesting electioneering developments in the last few years: microtargeting statistical methods and controlled, randomized experiments to predict cause and effect in political activity.
Obama’s 54-member analytics team—nicknamed Team Data—worked twenty-four hour days by the end of the campaign, using millions of dollars in research. The campaign’s analytic teams were able to micro-target persuadable voters to generate the margin of victory in some of the tightest battleground states. The focus on analytics allowed the Obama campaign to efficiently recruit volunteers, tailor e-mails, purchase ads, and raise money.
A Romney campaign supporter distributes signs
Another tool that the Obama campaign used was its “persuasion model,” which sifted through millions of registered voters in the Democratic National Committee’s database to locate those most likely to turn out and vote for the incumbent. Canvassers were then able to take this information and tailor their campaign scripts to individual voters based on their specific issues of interest. The campaign also used the Optimizer, a system developed by software engineers to collect loads of data on the pricing of television ads. The analytics team then scrutinized this data to search for efficiencies. Most of the data was taken from public voting records and responses voters provided to canvassers, rather than consumer data.
The Obama campaign’s analytics team wasn’t just similar to a tech company in their use of big data. They also sought to build a team that operated with a startup mentality by hiring top-notch engineers, data scientists, developers, and digital ad experts willing to work grueling hours. In a way, startups and political campaigns share a similar culture of dedication, passion, and initiative by all team members—an absolute must for success. We look forward to seeing what political campaigns of the future will look like as campaign strategists increasingly incorporate a data-driven and startup-influenced ethos.