How Obama’s Team Used Big Data to Rally Voters - MIT Technology Review
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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.
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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. 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.
How Obama's data crunchers helped him win
Election -- photos from the finish line Predicting turnout The 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. This was a huge advantage: 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.
The polling and voter-contact data were processed and reprocessed nightly to account for every imaginable scenario. And that is how we allocated resources.
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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.
Any insights were distorted by the artificial settings and by the tiny samples of demographic subgroups in traditional polls. And people have been doing that for decades! Experimenters would randomly assign voters to receive varied sequences of direct mail—four pieces on the same policy theme, each making a slightly different case for Obama—and then use ongoing survey calls to isolate the attributes of those whose opinions changed as a result.
The experiment revealed how much voter response differed by age, especially among women. Older women thought more highly of the policies when they received reminders about preventive care; younger women liked them more when they were told about contraceptive coverage and new rules that prohibited insurance companies from charging women more. The results were surprising. Those scores suggested that they probably shared Republican attitudes; but here was one thing that could pull them to Obama.
Traditionally, campaigns have restricted their persuasion efforts to channels like mass media or direct mail, where they can control presentation, language, and targeting.
Sending volunteers to persuade voters would mean forcing them to interact with opponents, or with voters who were undecided because they were alienated from politics on delicate issues like abortion.
They began sending trained volunteers to knock on doors or make phone calls with the objective of changing minds. That dramatic shift in the culture of electioneering was felt on the streets, but it was possible only because of advances in analytics. Likely Obama supporters would get regular reminders from their local field organizers, asking them to return their ballots, and, once they had, a message thanking them and proposing other ways to be involved in the campaign.
The local organizer would receive daily lists of the voters on his or her turf who had outstanding ballots so that the campaign could follow up with personal contact by phone or at the doorstep. Wagner, however, was turning his attention beyond the field.
Throughout the primaries, Romney had appeared to be the only Republican running a 21st-century campaign, methodically banking early votes in states like Florida and Ohio before his disorganized opponents could establish operations there.
Such techniques had offered George W. ByDemocrats had not only matched Republicans in adopting commercial marketing techniques; they had moved ahead by integrating methods developed in the social sciences. That was the structure Obama had abandoned after winning the nomination in Instead, they fixated on trying to unlock one big, persistent mystery, which Lundry framed this way: TargetPoint also integrated content collected from newspaper websites and closed-caption transcripts of broadcast programs.
Ultimately, Lundry wanted to assess the impact that each type of public attention had on what mattered most to them: He turned to vector autoregression models, which equities traders use to isolate the influence of single variables on market movements.
That informal conversation among political-class elites typically led to traditional print or broadcast press coverage one to two days later, and that, in turn, might have an impact on the horse race.
Those insights offered campaign officials a theory of information flows, but they provided no guidance in how to allocate campaign resources in order to win the Electoral College.
The goal was to try to divine the calculations behind those decisions. In early September, as part of his standard review, Lundry noticed that the week after the Democratic convention, Obama had aired 68 ads in Dothan, Alabama, a town near the Florida border. Even though the area was known to savvy ad buyers as one of the places where a media market crosses state lines, Dothan TV stations reached only about 9, Florida voters, and around 7, of them had voted for John McCain in But they were advertising there.
Already the Obama campaign was known for its relentless e-mails beseeching supporters to give their money or time, but this one offered something that intrigued Davidsen: With Narwhal, e-mail blasts asking people to volunteer could take their past donation history into consideration, and the algorithms determining how much a supporter would be asked to contribute could be shaped by knowledge about his or her reaction to previous solicitations. Now analysts could leverage personal data to identify the attributes of those who responded, and use that knowledge to refine subsequent appeals.
Television and radio ads had to be purchased by geographic zone, and the available data on who watches which channels or shows, collected by research firms like Nielsen and Scarborough, often included little more than viewer age and gender.
How you knit that together is a challenge. But when it came to buying media, such calculations had been simply impossible, because campaigns were unable to link what they knew about voters to what cable providers knew about their customers. Walsh says of the effort to reimagine the media-targeting process: It was to find out how many of our persuadable voters were watching those dayparts.
For privacy reasons, however, the information was not available at the individual level. The Obama campaign had created its own television ratings system, a kind of Nielsen in which the only viewers who mattered were those not yet fully committed to a presidential candidate.
But Davidsen had to get the information into a practical form by early May, when Obama strategists planned to start running their anti-Romney ads. She oversaw the development of a software platform the Obama staff called the Optimizer, which broke the day into 96 quarter-hour segments and assessed which time slots across 60 channels offered the greatest number of persuadable targets per dollar. By September, she had unlocked an even richer trove of data: Sometimes a national cable ad was a better bargain than a large number of local buys in the 66 media markets reaching battleground states.
But the occasional national buy also had other benefits. They had invested in their own media-intelligence platform, called Centraforce.
It used some of the same aggregated data sources that were feeding into the Optimizer, and at times both seemed to send the campaigns to the same unlikely ad blocks—for example, in reruns on TV Land.
The campaign had plenty of those, generated by a public-opinion team of eight outside firms, and new arrivals at the Chicago headquarters were shocked by the variegated breadth of the research that arrived on their desks daily. The lead pollster, Joel Benenson, had respondents write about their experiences. A quartet of polling firms were assigned specific states and asked to figure out which national themes fit best with local concerns.
But the campaign had to play defense, too. Simas would monitor Community conversations to see which news events penetrated voter consciousness. There were simply more undecided voters in such states—sometimes nearly twice as many as the traditional pollsters found. A basic methodological distinction explained this discrepancy: The rivalry between the two units trying to measure public opinion grew intense: Green Bay was the only media market in the state to experience such a shift, and there was no obvious explanation.
But it was hard to discount. Whereas a standard person statewide poll might have reached respondents in the Green Bay area, analytics was placing 5, calls in Wisconsin in each five-day cycle—and benefiting from tens of thousands of other field contacts—to produce microtargeting scores.
Analytics was talking to as many people in the Green Bay media market as traditional pollsters were talking to across Wisconsin every week.
In the end, Romney took the county For the most part, however, the analytic tables demonstrated how stable the electorate was, and how predictable individual voters could be. The analytic data offered a source of calm. Those who answered that question with a seven or below on a point scale were disregarded as not inclined to vote. As a result, the Republicans failed to account for voters that the Obama campaign could be mobilizing even if they looked to Election Day without enthusiasm or intensity.
Each day, the campaign overlaid the lists of early voters released by election authorities with its modeling scores to project how many votes they could claim as their own.
Wagner sorted them by microtargeting projections and found that 58, had individual support scores over That amounted to The numbers settled almost exactly where Wagner had said they would: The Legacy A few days after the election, as Florida authorities continued to count provisional ballots, a few staff members were directed, as four years before, to remain in Chicago.
Their instructions were to produce another post-mortem report summing up the lessons of the past year and a half. The undertaking was called the Legacy Project, a grandiose title inspired by the idea that the innovations of Obama should be translated not only to the campaign of the next Democratic candidate for president but also to governance.