How big data broke American politics

Political strategists once entered campaigns with a single basic assumption about partisanship: Elections would almost always be decided by about 20 percent of voters who fell somewhere in the ideological middle. By the late 1990s and early 2000s, that sliver of persuadable voters shrunk to about 10 percent.

But, thanks to the advent of what was first known as “micro-targeting,” campaign consultants realized that the easiest way to win wasn’t to persuade the folks in the middle at all. Instead, data could be used to activate every possible base voter and build a partisan firewall.

Why try to change the mind of one skeptic, the logic goes, when in the same amount of time you could make sure five core supporters commit to go to the polls?

And there is an added benefit to avoiding persuasion: By courting only true believers, candidates don’t have to promise the kind of “pragmatism” that avowed partisans label “squishiness.”

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