The Victory Lab (42 page)

Carson knew this would put a lot of pressure on the phone vendors who won Obama’s lucrative contracts to identify voters, and he worried about their quality. That corner of the political industry had earned a particular reputation for unscrupulous practices, relying on untrained and unenthusiastic call center personnel who were sloppy about how they recorded voters’ answers. Campaign staff had long suspected that operators sometimes just made up responses, especially when a voter hung up midway through a script and faking a few answers to the final questions meant not having to throw out the rest of a completed survey. Carson conceived a scheme that within Obama’s headquarters was likened to the reality show competition
Survivor
, and those outside it quickly understood why.

In the early summer, the campaign talked to ten of the party’s top phone vendors on a conference call and told them they were each getting 10 percent of the nominee’s business. Each firm had a different pricing scheme, but the vendors were not going to be judged on price or reputation,
as was typically the case. Instead, they were told, they would be tested against one another in real time. Every Sunday night, the Obama campaign would provide each of them a list of VAN identification codes and attached phone numbers, along with a script for callers to use. By midday on Friday, the phone vendors would return a spreadsheet of VAN IDs with the voters’ answers to the script questions. Each week, the campaign would send out a report to all the vendors that showed how they and their competitors had fared under a “cost-per-opinion” metric that calculated what Obama was actually paying for each call successfully completed. Any firm that underperformed would see their share split among competitors.

After a month, half of the phone vendors were gone. The decision had not been made entirely on relative costs-per-opinion, as they had been told it would be. Obama’s team had included a question at the end of each script, asking voters for their age, and often found that what came back from the vendors for that category didn’t match up with the date of birth on the voter file. None of the campaign officials who had privately accused phone vendors of fabricating data had ever thought to audit them in the midst of the campaign. There was no way, short of calling voters back and confirming their answers, to see if a call center had accurately tallied their candidate preference, but date of birth was an independently verifiable fact (and, since it came from government registration records, highly reliable). “It was something they couldn’t make up,” says Simon.

At the same time, two hundred headquarters staffers were instructed to devise a fictive alter ego that would be given a VAN record and placed, with the employee’s actual mobile number, on the lists given each week to the phone vendors. Luke Peterson, the database manager during the primaries, became “Joseph Ratzinger,” a pro-life hard-liner and political independent who was entirely undecided about whether to support Obama or McCain. Three or four times a day, Peterson’s phone would ring and he would answer as Ratzinger; his answers on abortion and his candidate preference would stay stable, but then he was invited to improvise his responses and have fun with accents. Afterward, Peterson would go online
and complete a short Web form rating the caller’s performance. Did he or she read the script accurately? Was the caller clear and polite?

Five vendors ended up winning a share of Obama’s business, and they already appreciated how much more it would demand of them than the typical campaign account. During the primaries, Strasma had treated these paid ID calls as roughly equal in value to the so-called field IDs that volunteers entered into the VAN; they all entered the algorithm interchangeably as indicators of voter support or enthusiasm. For the general election, the number of field IDs available for their calculations would only grow, as Obama’s new-media team was working to make it even easier for those willing to place phone calls to do it from their own homes. The new-media team built a calling tool into a prominent feature of the MyBarackObama website, which would automatically assign a volunteer to voters in the nearest battleground state and produce an appropriate script for them to read. They constantly tweaked the design to reduce the number of clicks necessary to actually dial a call, and enlisted a ten-thousand-member National Call Team of committed volunteers who eventually made three million calls through the interface. But over the course of the summer Obama’s analysts realized that their candidate was drawing more support among these contacts than ones reached by paid phone banks; people seemed wary of insulting a volunteer canvasser by announcing they supported another candidate, and often lied to say they were undecided instead. The targeting desk decided that the algorithms would have to weight the paid calls far more heavily than the field IDs.

As Strasma explained in Portland, he had designed a system to turn virtual IDs into a continuous process, where individual probabilities moved in a way that accurately reflected that a person’s propensity for picking a certain candidate, or voting at all, was subject to near-constant flux. He imagined doing for microtargeting what tracking polls had for the once-static study of public opinion. Pioneered in the 1970s by Bob Teeter and Fred Steeper, those continuous small-sample polls relied on several hundred calls every single night, with each batch of new opinions rolling over
one another like lapping waves, so that the older ones bubbled away as they were replaced. They lacked nuance—the calls focused primarily on candidate support—but they captured movement at a price that major campaigns and media organizations could afford.

Already in the primary season, Strasma had seen a hint of how the aggregation of individual microtargeting scores could offer a substitute for polls as a way of tracking opinion shifts. Instead of merely relying on a small sample of voters to say what they felt now, Strasma could use the algorithm to extrapolate how every voter on the file might be moving, then look for patterns in their movement. In early 2008, in states like Iowa that made it easy for non-Democrats to vote in the Democratic primaries, Republican support scores for Obama were always higher than those of his opponents. But in the run-up to the Ohio primary, those scores quickly flipped, and Clinton started pulling higher support scores among Republicans. It wasn’t tough to figure out why. On his radio show, Rush Limbaugh was promoting a plan he called “Operation Chaos,” to encourage Republicans to cast votes for Clinton as a way of fomenting further conflict within the opposition. Many Democrats were skeptical the stunt would have much impact, but Strasma’s changing scores confirmed that voters actually seemed to be following Limbaugh’s orders. After Ohio, Obama’s campaign all but abandoned its outreach to Republicans.

Strasma believed his algorithm could help Obama make similar strategic decisions in the general election, as well. Typically a campaign would plan to collect a massive batch of paid IDs in the summer so that they could be used to separate persuadable voters from get-out-the-vote targets with enough time to run an aggressive program making the case to the former. But Strasma pushed Plouffe to take the budget for those IDs and spread them out over the entirety of the campaign; he knew Obama’s field team would lose some of the precision that comes from having hard IDs on voters but they could make it up with more refined predictive models. Strasma proposed a two-tiered system of IDs that echoed the way the Census monitored population changes. Every week, the Obama campaign
would hire call centers to do between 1,000 and 2,000 of what Strasma called long-form IDs per battleground state, which would be closer to a traditional poll, with questions about issues and campaign dynamics. At the same time, the campaign would be doing between 5,000 and 10,000 short-form IDs in each state, quick calls that through as few as two questions did little more than gauge a voter’s candidate preference and likelihood of voting. One-quarter of those would always be re-IDs, voters who had been previously contacted and were called again.

After the algorithms worked through the new round of weekly IDs, they would drop a new set of support and turnout scores on every voter’s record in the VAN, each of them represented as a percentage probability. After four weeks, Strasma was able to see which voters were moving between candidates. Eventually they had a large enough sample of those who changed from McCain to Obama, and vice versa, that the campaign was able to create a model of these voters they called “shifters.” It allowed the campaign to refine its category of “undecided,” a catch-all description that long frustrated political scientists and psychologists because it was applied equally to voters who hadn’t made up their minds, weren’t paying attention, were trying to weigh competing values, or were simply unwilling to share with a stranger what many considered a private matter. Someone who was undecided in June was probably a very different type of voter than one who was undecided in October. Using algorithms to find other undecided voters who looked like shifters (and determine which direction they were likely to go) would help the Obama campaign know which ones were worth targeting, and when to do so.

By the time of the Republican convention in early September, the Obama campaign was placing well over one hundred thousand paid ID calls a week nationwide, with all the data feeding into Strasma’s computers. When McCain picked Alaska governor Sarah Palin as his running mate, Obama’s strategists were befuddled: they thought the Republican had been gaining traction by highlighting Obama’s thin résumé, and he now seemed to be sacrificing that argument by putting forward their own neophyte. But
one week after the Republican convention, Strasma saw the first sign that McCain’s move might be paying off when the first round of post-Palin IDs came back from phone banks. People were identifying themselves as pro-McCain at a higher rate than their scores suggested they should have been. Strasma bore down into the numbers and saw that the phenomenon was particularly strong among women. Campaign strategists worried that McCain and Palin, running as “two mavericks,” may have been proving themselves successful at seizing Obama’s themes of change and reform.

When the next round of IDs came in, two weeks after the Palin nomination, the IDs told a different story. The models had begun to integrate the increased levels of support for McCain’s ticket, but now the IDs were heading in the other direction, underperforming the scores, especially among Republican women. The modeling scores hadn’t caught up to what voters thought of Palin. The disconnect between the two suggested that Palin’s selection had offered little more than a temporary bump, as opposed to the permanent boost that McCain’s advisers had anticipated. “She ended up being a sugar high for them,” says Giangreco, “and she went away as quickly as she came.”

That eventually became conventional wisdom among media and the campaigns themselves, but Strasma saw it well ahead of the curve: his perfectly efficient loop of IDs cycling through the algorithm had proven itself a useful tool in the arsenal of measuring public opinion at a high velocity. “You would see things faster than the polling would come back,” says Freeman. Once the campaign had developed its modeling score for the action of shifting, it became possible not only to predict what views a voter had but also individual susceptibility to changing them at a given point in the election year. Strasma believed that this predictive modeling gave Obama’s staff the tools of the fortune-teller. “We determined that, down the line, they were going to break for us,” he says. “We knew who these people were going to vote for before they decided.” Now the campaign had to make sure it knew how to reach them.

THE SOUL OF A NEW MACHINE

T
he
buses running along the number 6 line in Akron’s Metro Regional Transit Authority system often begin their inbound morning trips completely empty. The line’s eastern terminus sits along the southwestern edge of that Ohio city, on the sidewalk in front of a Goodwill store in a forlorn shopping plaza so perfectly placeless that the pollster Peter Hart has maintained a permanent storefront facing the JCPenney to host focus groups monitoring a microcosm of the changing American mind.

The bus pulls out of the parking lot and turns past the Akron Springfield Assembly of God church, whose vast grass lawn can often find itself studded with alternating signs promising such varied civic activities as a local Oktoberfest and a Red Cross blood drive. The 6 bus ascends past the oaks and maples that canopy the single-family homes of
middle-class, largely white Ellet, and down less verdant stretches of East Market Street that mark the southern edge of Middlebury, one of the city’s oldest and
most racially mixed neighborhoods. Farther on, the route passes the world headquarters of Goodyear, the tire maker that once made Akron an industrial boomtown, where salarymen pace the sidewalk as they savor their rationed minutes in nicotine’s company.

Along the way, the bus gathers passengers—hospital orderlies in teal scrubs, elderly shoppers, students with backpacks and collapsing eyelids—as it rumbles toward the modest skyline of Ohio’s fifth-largest city. Two-thirds of the way along its forty-minute route to the Akron Transit Center, the 6 begins to descend the gentle slope that pulls Akron’s downtown toward the Ohio & Erie Canal, on which it was founded. The bus disgorges its commuters at the major institutions that keep Akron alive—the orderlies report for their shifts at the Akron City Hospital, students stumble out at the University of Akron, office workers scurry toward the municipal building and courthouse—even as the factories that once sustained the “Rubber Capital of the World” have relocated elsewhere.