Data Mining gives GOP an edge

The LA Times has an article on how the Republicans have collected life-style data on potential voters that allow them to identify likely Republican and Democratic voters and target appropriate messages to each so as to get out the vote for their candidates. (Ruy Teixeira directed me to this article.)

A deeper look at her lifestyle and politics reveals a voter who might be persuaded to switch sides. Among the clues: she [Felicia Hill - Ohio African American] is a church member uneasy about abortion; she lives in a growing suburb and she sent her children to a private school.

Hill and millions of other would-be Bush backers in closely contested states were identified by a GOP database that culled information ranging from the political basics, like party registration, to the personal, such as the cars they drive, the drinks they buy, even the features they order on their phone lines. The "micro-targeting" effort was so effective that the party credited it with helping to secure Bush's reelection.

In Ohio, which tipped the election to Bush, the Republican strategy helped boost African American support for the president by seven percentage points over his 2000 performance, securing the state for the president. It drew millions of Republican voters to the polls in every battleground state.

Nationally, Republicans said, the targeting produced a 10 percentage point increase for Bush among evangelicals, nine points among Latinos, four points in big cities, three points in labor-union households and five points among Catholics — all groups that were wooed by both parties.

I had heard about this technology a few years ago in a data processing course. The technology is there and the marketing is a set of clearly established procedures. The Democrats need to come up to speed in spite of the expense.

So what is data mining? Here is a decsription from Kurt Thearling.

Data Mining, if you haven't heard of it before, is the automated extraction of hidden predictive information from databases.

Data mining software allows users to analyze large databases to solve business decision problems. Data mining is, in some ways, an extension of statistics, with a few artificial intelligence and machine learning twists thrown in. Like statistics, data mining is not a business solution, it is just a technology. For example, consider a catalog retailer who needs to decide who should receive information about a new product. The information operated on by the data mining process is contained in a historical database of previous interactions with customers and the features associated with the customers, such as age, zip code, their responses. The data mining software would use this historical information to build a model of customer behavior that could be used to predict which customers would be likely to respond to the new product. By using this information a marketing manager can select only the customers who are most likely to respond. The operational business software can then feed the results of the decision to the appropriate touch point systems (call centers, direct mail, web servers, email systems, etc.) so that the right customers receive the right offers.

This was also the technology at the heart of Admiral Poindexter's program at the Pentagon known as Total Information Awareness for identifying and tracking potential terrorists.

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See also
How will Dems win the Country back? for a discussion of other efforts needed by Democrats and links to prior related stories.