The Victory Lab (20 page)

After two weeks, Simulmatics returned its report on “
the consequences of embitterment of the religious issue” to Robert F. Kennedy,
each copy numbered to guard against leaks of a document considered highly sensitive.
Inside was a ranking of thirty-two non-southern states in their likelihood of going for Kennedy if he directly addressed the Catholic question. Eleven states, they projected, would move away from Kennedy on religion alone, totaling 122 electoral votes. But the issue could pull six states, including three out of the four largest in the country, into the Democratic column. Together they were worth 132 electoral votes. “Kennedy today has lost the bulk of the votes he would lose if the election campaign were to be embittered by the issue of anti-Catholicism,” the Simulmatics report stated. “The simulation shows that there has already been a serious defection from Kennedy by Protestant voters. Under these circumstances, it makes no sense to brush the religious issue under the rug. Kennedy has already suffered the disadvantages of the issue even though it is not embittered now—and without receiving compensating advantages inherent in it.” Less than three weeks after his brother received that advice, the Democratic nominee traveled to Houston to talk about his faith before a gathering of ministers. “I believe in an America where religious intolerance will someday end,” Kennedy said, “where there is no Catholic vote, no anti-Catholic vote, no bloc voting of any kind.”

It was an ironic aspiration for Kennedy, since his campaign’s embrace of Simulmatics reflected by far the most serious effort ever to develop a science of bloc voting. Pool did not know if their math had changed the campaign’s calculus around the Houston speech, or if any of the three reports that Simulmatics delivered (others concerned Kennedy’s image, Nixon’s image, and the role of foreign policy as an issue) informed strategic decisions. “They were seen during the campaign by perhaps a dozen to fifteen key decision makers, but they were read intelligently by these talented and literate men,” Pool and his colleagues wrote. Even if their analysis had not shaped campaign plans, the returns in November offered some validation for their technique.
Pool calculated that Simulmatics’ state rankings had an 82 percent correlation with the actual vote.

When the existence of the 480 voter-types was reported after the election, the Simulmatics project was heralded as ushering in a new era of space-age politics, as
Harper’s
described it in a story headlined “The People-Machine.” “
This is the A-bomb of the social sciences,” Lasswell said, likening it to the first self-sustaining nuclear chain reaction, conducted by wartime Manhattan Project researchers at an abandoned University of Chicago football stadium. “The breakthrough here is comparable to what happened at Stagg Field.” Newspapers and wire services covered the
Harper’s
report as news, even as Kennedy’s spokesman denied the existence of the Simulmatics reports altogether. “
We did not use the machine,” press secretary Pierre Salinger lied to UPI.

Even though Burdick wrote affectionately about the scholars looking to bring new rigor to smoke-filled political backrooms,
The 480
was often read as a cautionary tale about the ability of campaigns to be cynically mechanized at the expense of real people. Pool may have been able to disassemble the electorate into microscopic pieces, but the tools for speaking to voters—national advertising, broadcast television, and speeches covered by metropolitan and regional papers—still existed only on a macro scale. Simulmatics had a good idea of knowing what a small-city, Catholic, Democratic, lower-income woman was likely to think of tax policy, but it
offered no guidance to a campaign that wanted to locate members of that category and speak to them directly.

New sources of granular data would make that easier. In 1962, the U.S. Postal Service rolled out its Zone Improvement Plan, which split the country into thirty-six thousand zones and assigned each a five-digit code to help post offices automate their procedures. Soon businesses began using these ZIP codes to presort their catalogs and magazines, and as the direct-mail business boomed these numerical anchors became a useful way to root consumer data in place: they were more compact than counties or towns, the closest thing to quantifying neighborhoods.
In 1974, computer scientist Jonathan Robbin used research from
customer surveys and block-level Census data to compile 535 demographic variables that could be attached to each ZIP code. Those boundaries had been drawn to aid mail delivery, but Robbin’s Claritas Cluster System used the arbitrary lines to fence people in by their common lifestyle traits.
Robbin’s computers assigned each ZIP code to one of forty different clusters, which he gave colorful names, from Furs & Station Wagons (“new money in metropolitan bedroom suburbs”) to Norma Rae–Ville (“lower middle-class milltowns and industrial suburbs, primarily in the South”). The profiles became popular with marketers, from Colgate-Palmolive to
Time
, who relied on Robbin’s data and vivid social portraiture as a new lens onto America: a way of visualizing their consumers, and then knowing where they lived. Robbin soon became known as the “
King of the Zip Codes.”

In 1978, he persuaded Matt Reese, the already legendary Democratic voter contact consultant, that
his clustering system could be used for politics. That year, Reese was working on behalf of the United Labor Committee of Missouri to beat back a proposed right-to-work referendum in Missouri, an issue that did not fall neatly along partisan lines. Reese hired Democratic pollster Bill Hamilton to survey 1,367 Missouri voters about their political views, and then used the respondents’ addresses to identify them with one of Claritas’s clusters. Hamilton’s polls found eighteen clusters rich with persuadable voters, building a list of 595,000 targets, and identified the
most promising arguments for each. Those who lived in areas Claritas had designated as Grain Belt clusters received Reese’s “pocketbook argument” (which emphasized that right-to-work laws would also hurt those farmers whose customers belonged to unions) while those in Coalburg & Coaltown clusters saw mail with a “status quo” message (pointing out that neighboring right-to-work states had impoverished economies). “
The campaign was so carefully targeted,” Hamilton said, “that one resident of Springfield, Missouri, might think that defeating the initiative was the most important thing since the invention of sliced bread. Meanwhile, a few blocks away, someone might not even know the initiative was on the ballot.”

Upon defeating the Missouri referendum, Reese credited the clustering method (which had cost three hundred thousand dollars, one-fifth of the labor committee’s budget) that he called “the new magic.” Reese and Eddie Mahe Jr., a former RNC deputy chairman and leading Republican consultant, joined forces to become bipartisan evangelists for clusters in Washington. The clusters seemed ready-made for a new decade that would, at least in the popular imagination, be remembered for its consumerism. Claritas was selling a map key for decoding the politics of a mobile, postindustrial America where even the middle classes had the means to self-segregate according to their tastes and interests, and people were more likely to identify themselves as consumers than as workers. In director Sidney Lumet’s 1986 film
Power
, a mercenary political consultant played by Richard Gere—always shuttling by private jet to prop up Latin American strongmen with media manipulation or lifeless domestic campaigns with disingenuously action-packed TV spots—introduces clusters to his clients. “We’ve concluded a high favorable is Pools & Patios: suburban, white-collar, married twenty-five- to forty-nine-year-olds,” Gere’s character tells a New Mexico gubernatorial candidate. “We tailor the mail and phone pitches based on what we know is already bothering them. But the really exciting stuff comes when I work out a simulation model. That’s when you tell me what you’re thinking of saying and I tell you how they’re going to react.”

At the same time, the Times Mirror Company was deep in a three-year statistical project to split the electorate into eleven clusters it called “typology groups.” While the party identity of the 4,244 Americans whom Gallup surveyed played an important role in defining the clusters, the report issued in September 1987—as both parties wrestled with open primaries to find nominees to succeed Ronald Reagan—radically avoided using the language of an ideological continuum to define any of them. “
In 1987, the conventional labels of ‘liberal’ and ‘conservative’ are about as relevant as the words ‘Whig’ and ‘Federalist,’ ” the report’s authors declared. “We will divide that electorate into distinct, new constituencies and identify the fundamental outlooks on life and major institutions that animate virtually all American political behavior.” Two of the clusters were distinctly Republican (Enterprisers and Moralists), four Democratic (New Dealers, Sixties Democrats, the Partisan Poor, and the Passive Poor), and two leaning in each direction (Upbeats and Disaffecteds towards the Republicans, Seculars and Followers towards the Democrats). Eleven percent of American adults were found to be fully, and seemingly permanently, detached from politics; Times Mirror called them Bystanders.

And yet even as clusters infiltrated pop culture and public opinion research, they never found a steady place in the political arsenal. Reese and Mahe, who had negotiated an exclusive franchise to market Claritas to political customers, struggled to translate the clusters so they would be easier for Washington hands to grasp. “The names of the groups didn’t resonate politically,” says Mahe. “The descriptions were written with marketing in mind.” He and Reese rewrote profiles so they invoked political behaviors, with terms like
conservative
and
swing voter
, and emphasized that the clusters would nonetheless be most useful to campaigns not for visualizing types of voters but for locating them geographically. Still they were unable to sell clustering to any presidential candidates in 1980 or 1984. It was an expensive proposition for a campaign, and only a handful of congressional candidates ever bought it.
By the end of the 1980s, Reese and Mahe had let their Claritas franchise expire.

Those who looked closely at the categories of data being used to shape the clusters were shocked to see that they didn’t include markers for race or ethnicity as a demographic variable.
A two-page summary of Claritas’s “Downtown Dixie-Style” cluster recorded that its residents, in working-class neighborhoods of cities such as Fayetteville, North Carolina, and Selma, Alabama, were disproportionately devoted consumers of soul records, malt liquor, and
Jet
(and infrequent overnight campers,
Ms
. readers, or frozen-yogurt eaters), but never emphasized the one attribute they shared above all else: they were overwhelmingly African-American. “I’d have to sit through all these pitches where they’d say ‘We know this stuff better than you guys, what we do applies to your work, we know how to do it,’ ” says Tom Bonier, who as one of the lead analysts for the National Committee for an Effective Congress was invited to observe marketers’ presentations to the DNC and the party’s campaign committees. “But the big thing they didn’t use, which is sensitive in the corporate world but not in the political world: they don’t use race in their clusters, because to them it’s distasteful whereas in politics it’s an accepted fact.”

When pollsters tested the clusters, by looking at how members of different groups answered political questions, they realized that they didn’t add much to the basic mix of precinct-based targeting and polling to find basic demographic splits. The arbitrary lines around ZIP codes had forced Claritas to effectively compromise when it tried to summarize an area’s character, defining it only by its dominant lifestyle traits. What about all the people who didn’t match the prevailing consumer sensibility? (One political data expert stumbled upon a glaring example of the risk of treating everyone in a cluster as the same. The areas that Claritas called Pools & Patios included significant populations that looked nothing like the people with whom they shared an address: those who lived in the ZIP code in order to clean their neighbors’ pools and patios.) It may be a sensible business decision to put a GapKids in a New Homesteaders neighborhood that is 55 percent childless households, but it would be malpractice for a Republican campaign manager to run a GOTV operation in that same area
if it is 55 percent Democratic. “While they may have worked very well for selling Sonys or Toyotas or Mercedeses or Fords, they didn’t work very well for the politics. They didn’t discriminate that well,” says pollster Mark Mellman, who began experimenting with clusters in 1996. “You’re stuck with how they divide people for marketing purposes, and those marketing purposes might not overlay with political purposes. The truth is the political purposes from one election to another may vary.”

YET WHEN THE MICHIGAN REPUBLICAN PARTY
approached Gage in 2001 about moving beyond precinct targeting, his first instinct, too, was Claritas. He ordered up the profiles and commissioned a poll to survey two hundred people in each of its clusters. Initially, Gage encountered many of the same shortcomings others had faced before him. When he looked more closely at the components of the clusters, however, Gage saw that all the ingredients should be available to him in raw form. Gage could reassemble that raw data into his own clusters, purpose-built for nothing other than politics. Then, he concluded, he could unshackle the clusters from the arbitrary geography of ZIP codes. Gage could put people into the clusters that really suited them—based on their political views and behavior—regardless of where they lived.