Saturday Learning Series - Data Modeling and Mining

Stay with me on this one. I can't stress enough how important this episode is for the conservative movement.   In the past I've argued that there is a much smarter way to use data in everything, but it's particularly true in politics.  Conservatives can argue until they are blue (or red) in the face about what could have defeated president Obama in the 2012 election, or what is needed to win in 2016, but what made a big difference for Obama was targeted tactical efforts in key areas, maximizing their results to spectacular effect.

Barack Obama won the 2012 presidential election, defeating Mitt Romney in nearly all battleground states, securing a total of 332 electoral votes and winning 51% of the popular vote. Following the election, several prominent media outlets reported the Obama campaign’s effective mining of the large databases of voter information was a major factor in the president’s victory. In fact, during the election, Time Magazine interviewed several of the Obama campaign’s “data crunches” and estimated their efforts “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.” Obama strategist David Axelrod told news reporters “nothing happened on election night that surprised me — nothing. Every single domino that turned over was in keeping with the model that our folks had projected.”

...Data was continually collected through cookies and tracker programs on Obama’s website and social media apps. Using data mining, the Obama campaign’s data scientists were able to comb through all the information to discover important patterns and draw conclusions about potential voters. They assigned potential swing state voters numbers of a scale of 1 to 100 in four metrics: the likelihood that they would support Mr. Obama, the likelihood they would show up at the polls, the likelihood an Obama supporter who did not consistently vote could be motivated to go to the polls, and finally, how persuadable someone was by a conversation on a particular issue.

The Obama campaign then utilized advanced statistical algorithms to run test models predicting what actions or messages would persuade the most voters to swing democratic.

...David Axelrod stated that because of the 2012 results he would: “invest in people who understand where the technology is going and what the potential will be by 2016 for communications, for targeting, for mining data, to make precision possible in terms of both persuasion and mobilization.” Because of the crucial role data mining played in Obama’s victory, “guys sitting in a back room smoking cigars, saying ‘We always buy 60 Minutes’ is over.” Fundamentals and gut feelings are being replaced by the information driven insights of data scientists and technology.

As much as we all hold considerable antipathy towards Team Chicago, we can still learn from their smart election moves -in fact, we have to learn from them, or perish.

With that in mind, here's a backgrounder on Data Mining, starting with a primer and the second video diving into some more detail.

And now a little bit scarier, a more detailed but still high level introduction.