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 Billion
For 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 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. 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
