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Democrats, continued from page 17 know who they are. Both national parties already have toyed with voter targeting, incorporating demographic and consumer data into their voter files. Thus far, however, Republicans have been far more adept at utilizing the data. Beatty was wowed by the ingenuity of the Bush-Cheney 2004 campaign that presidential adviser Karl Rove devised. Rove recognized that conservative religious voters were severely underrepresented in the 2000 election, and used data mining to identify these voters and win them over in key battleground states, particularly Ohio. As Beatty will tell you, one of the reasons the exit polls were so wrong on election day 2004 was because the BushCheney campaign simply knew who its voters were better than exit-polling agencies did. Another recent example of GOP data mining prowess was the 2005 vote on a Texas constitutional amendment to ban same-sex marriage. For Beatty, the reason the amendment won 76 percent of the votea tally that shocked some progressiveswas evident in the data. Conservative religious groups rolled out a strong targeting effort to uncover and attract new voters who would sup port a ban on gay marriage. “It had the largest turnout in a constitutional amendment election since 1990,” he says. “Twenty-five percent of those people had never voted in a general election in their lives.” Many of those new religious voters look enticing to Gov. Rick Perry’s re-election campaign. Perry was a high-profile supporter of the ban. Thanks to targeting in the constitutional amendment election, the Perry folks now know exactly which voters to go after this fall. Beatty believes that Democrats must be similarly ambitious. “I’m tired of hearing this thing that, ‘Well, we just have to wait for the census to turn around:” he says, referring to the conventional wisdom that an emerging Latino majority in Texas eventually will propel Democrats back into power. Voter targeting, he contends, can speed up the process. 0 n a July afternoon, Beatty settles down in front of his PC to demonstrate how data mining works. His home office occupies a small corner of his South Austin bungalow. A small blizzard of cigarette ash covers his workstation and keyboard. Smoldering Camel in one hand, mouse in the other, Beatty opens a software program called SPSS. Rows of numbers appear on the screen. This is raw voter data for Congressional District 14, which Beatty is analyzing to predict how the Southeast Texas area currently represented by Congressman Ron Paulwill vote in the upcoming governor’s race. What separates Beatty’s work from traditional voter identification techniques is the level of detail. The Democratic Party’s tried-and-true, precinct-based approach ends with a person’s voting history; Beatty’s analysis begins there. He takes the standard voter file, and “I add to that 10 to 15 commercial variablesare they a homeowner or renter? How old are their cars?” For the same reasons that shopping at Banana Republic may mean you receive the Pottery Barn catalog in the mail a few weeks later, political campaigns can obtain reams of consumer and demographic information about potential voters. These data troveswhich can list everything from the nonprofits you support to the magazines you receive in the mailare relatively easy to obtain. If not enough commercial data is available, a campaign can call a household to gain more information. Beatty then adds census information to the mix: How much do they earn? Married or single? Have kids or not? What race are they? Beatty runs the data through a series of complex analytic models on the computer. The software extrapolates from his sample to predict how people might vote. When the predictions prove to be mostly accurate, he groups voters by household, assigning each a house identification number based on address. So-called “householding” of voters is important, Beatty contends, because people’s living environment affects their voting. Is a likely Democratic voter married to a Republican? Is a 20-year-old living at home with two Democratic parents? Is a soft Democratic voter living with a probable GOP voter? All these change the formulas. With enough data, Beatty can produce for the campaign a detailed demographic portrait of the district. He also calculates two probabilities for 30 THE TEXAS OBSERVER SEPTEMBER 8, 2006