In late spring, the backroom number crunchers who powered Barack Obama’s campaign to victory noticed that George Clooney had an almost gravitational tug on West Coast females ages 40 to 49. The women were far and away the single demographic group most likely to hand over cash, for a chance to dine in Hollywood with Clooney — and Obama.
So as they did with all the other data collected, stored and analyzed in the two-year drive for re-election, Obama’s top campaign aides decided to put this insight to use. They sought out an East Coast celebrity who had similar appeal among the same demographic, aiming to replicate the millions of dollars produced by the Clooney contest. “We were blessed with an overflowing menu of options, but we chose Sarah Jessica Parker,” explains a senior campaign adviser. And so the next Dinner with Barack contest was born: a chance to eat at Parker’s West Village brownstone.
For the general public, there was no way to know that the idea for the Parker contest had come from a data-mining discovery about some supporters: affection for contests, small dinners and celebrity. But from the beginning, campaign manager Jim Messina had promised a totally different, metric-driven kind of campaign in which politics was the goal but political instincts might not be the means. “We are going to measure every single thing in this campaign,” he said after taking the job. He hired an analytics department five times as large as that of the 2008 operation, with an official “chief scientist” for the Chicago headquarters named Rayid Ghani, who in a previous life crunched huge data sets to, among other things, maximize the efficiency of supermarket sales promotions.
Exactly what that team of dozens of data crunchers was doing, however, was a closely held secret. “They are our nuclear codes,” campaign spokesman Ben LaBolt would say when asked about the efforts. Around the office, data-mining experiments were given mysterious code names such as Narwhal and Dreamcatcher. The team even worked at a remove from the rest of the campaign staff, setting up shop in a windowless room at the north end of the vast headquarters office. The “scientists” created regular briefings on their work for the President and top aides in the White House’s Roosevelt Room, but public details were in short supply as the campaign guarded what it believed to be its biggest institutional advantage over Mitt Romney’s campaign: its data.
On Nov. 4, a group of senior campaign advisers agreed to describe their cutting-edge efforts with TIME on the condition that they not be named and that the information not be published until after the winner was declared. What they revealed as they pulled back the curtain was a massive data effort that helped Obama raise $1 billion, remade the process of targeting TV ads and created detailed models of swing-state voters that could be used to increase the effectiveness of everything from phone calls and door knocks to direct mailings and social media.
How to Raise $1 BillionFor all the praise Obama’s team won in 2008 for its high-tech wizardry, its success masked a huge weakness: too many databases. Back then, volunteers making phone calls through the Obama website were working off lists that differed from the lists used by callers in the campaign office. Get-out-the-vote lists were never reconciled with fundraising lists. It was like the FBI and the CIA before 9/11: the two camps never shared data. “We analyzed very early that the problem in Democratic politics was you had databases all over the place,” said one of the officials. “None of them talked to each other.” So over the first 18 months, the campaign started over, creating a single massive system that could merge the information collected from pollsters, fundraisers, field workers and consumer databases as well as social-media and mobile contacts with the main Democratic voter files in the swing states.
The new megafile didn’t just tell the campaign how to find voters and get their attention; it also allowed the number crunchers to run tests predicting which types of people would be persuaded by certain kinds of appeals. Call lists in field offices, for instance, didn’t just list names and numbers; they also ranked names in order of their persuadability, with the campaign’s most important priorities first. About 75% of the determining factors were basics like age, sex, race, neighborhood and voting record. Consumer data about voters helped round out the picture. “We could [predict] people who were going to give online. We could model people who were going to give through mail. We could model volunteers,” said one of the senior advisers about the predictive profiles built by the data. “In the end, modeling became something way bigger for us in ’12 than in ’08 because it made our time more efficient.”
Early on, for example, the campaign discovered that people who had unsubscribed from the 2008 campaign e-mail lists were top targets, among the easiest to pull back into the fold with some personal attention. The strategists fashioned tests for specific demographic groups, trying out message scripts that they could then apply. They tested how much better a call from a local volunteer would do than a call from a volunteer from a non–swing state like California. As Messina had promised, assumptions were rarely left in place without
numbers to back them up.The new megafile also allowed the campaign to raise more money than it once thought possible. Until August, everyone in the Obama orbit had protested loudly that the campaign would not be able to reach the mythical $1 billion fundraising goal. “We had big fights because we wouldn’t even accept a goal in the 900s,” said one of the senior officials who was intimately involved in the process. “And then the Internet exploded over the summer,” said another.
A large portion of the cash raised online came through an intricate, metric-driven e-mail campaign in which dozens of fundraising appeals went out each day. Here again, data collection and analysis were paramount. Many of the e-mails sent to supporters were just tests, with different subject lines, senders and messages. Inside the campaign, there were office pools on which combination would raise the most money, and often the pools got it wrong. Michelle Obama’s e-mails performed best in the spring, and at times, campaign boss Messina performed better than Vice President Joe Biden. In many cases, the top performers raised 10 times as much money for the campaign as the underperformers.
Chicago discovered that people who signed up for the campaign’s Quick Donate program, which allowed repeat giving online or via text message without having to re-enter credit-card information, gave about four times as much as other donors. So the program was expanded and incentivized. By the end of October, Quick Donate had become a big part of the campaign’s messaging to supporters, and first-time donors were offered a free bumper sticker to sign up.
Predicting TurnoutThe magic tricks that opened wallets were then repurposed to turn out votes. The analytics team used four streams of polling data to build a detailed picture of voters in key states. In the past month, said one official, the analytics team had polling data from about 29,000 people in Ohio alone — a whopping sample that composed nearly half of 1% of all voters there — allowing for deep dives into exactly where each demographic and regional group was trending at any given moment. This was a huge advantage: when polls started to slip after the first debate, they could check to see which voters were changing sides and which were not.
It was this database that helped steady campaign aides in October’s choppy waters, assuring them that most of the Ohioans in motion were not Obama backers but likely Romney supporters whom Romney had lost because of his September blunders. “We were much calmer than others,” said one of the officials. The polling and voter-contact data were processed and reprocessed nightly to account for every imaginable scenario. “We ran the election 66,000 times every night,” said a senior official, describing the computer simulations the campaign ran to figure out Obama’s odds of winning each swing state. “And every morning we got the spit-out — here are your chances of winning these states. And that is how we allocated resources.”
Online, the get-out-the-vote effort continued with a first-ever attempt at using Facebook on a mass scale to replicate the door-knocking efforts of field organizers. In the final weeks of the campaign, people who had downloaded an app were sent messages with pictures of their friends in swing states. They were told to click a button to automatically urge those targeted voters to take certain actions, such as registering to vote, voting early or getting to the polls. The campaign found that roughly 1 in 5 people contacted by a Facebook pal acted on the request, in large part because the message came from someone they knew.
Data helped drive the campaign’s ad buying too. Rather than rely on outside media consultants to decide where ads should run, Messina based his purchases on the massive internal data sets. “We were able to put our target voters through some really complicated modeling, to say, O.K., if Miami-Dade women under 35 are the targets, [here is] how to reach them,” said one official. As a result, the campaign bought ads to air during unconventional programming, like
Sons of Anarchy,
The Walking Dead and
Don’t Trust the B—- in Apt. 23, skirting the traditional route of buying ads next to local news programming. How much more efficient was the Obama campaign of 2012 than 2008 at ad buying? Chicago has a number for that: “On TV we were able to buy 14% more efficiently … to make sure we were talking to our persuadable voters,” the same official said.
The numbers also led the campaign to escort their man down roads not usually taken in the late stages of a presidential campaign. In August, Obama decided to answer questions on the social news website Reddit, which many of the President’s senior aides did not know about. “Why did we put Barack Obama on Reddit?” an official asked rhetorically. “Because a whole bunch of our turnout targets were on Reddit.”
That data-driven decisionmaking played a huge role in creating a second term for the 44th President and will be one of the more closely studied elements of the 2012 cycle. It’s another sign that the role of the campaign pros in Washington who make decisions on hunches and experience is rapidly dwindling, being replaced by the work of quants and computer coders who can crack massive data sets for insight. As one official put it, the time of “guys sitting in a back room smoking cigars, saying ‘We always buy
60 Minutes’” is over. In politics, the era of big data has arrived.
Rubén Weinsteiner
