Team Clinton’s GOTV effort got out a lot of votes … for Trump
According to the Huffington Post:
As the post-election day hangover wears off, an examination of the mechanics behind the Clinton’s get out the vote efforts ― reaching out to Clinton voters in key states at the door, on the phone or by text messages ― reveals evidence of what appears to be a pretty shocking truth.
Clinton volunteers were inadvertently turning out Trump voters.
Possibly in significant numbers.
What went wrong?
Obviously, Team Clinton doesn’t follow the HomaFiles.
Too bad for them, we were all over this one in a post titled: Trump : “Data analytics is overrated” … could he be right?
Let’s flashback to August 2, 2016 ….
Last week, the WSJ ran an opinion piece: Trump’s Big Data Gamble.
The punch line: “While Donald tweets to the masses, Hillary will be precisely targeting persuadable voters.”
Advantage Hillary, right?
Maybe. Maybe not.
In an AP interview, Trump said that he “always thought that it (meaning data analytics) was overrated” and, accordingly, he’ll spend limited money on data operations to identify and track potential voters and to model various turnout scenarios that could give him the 270 Electoral College votes needed to win the presidency.
He’s moving away from the model Obama used successfully in his 2008 and 2012 wins, and the one that likely Democratic nominee Hillary Clinton is trying to replicate, including hiring many of the staff that worked for Obama in his “Victory Lab”.
A data-light strategy may sound very old-school in the era of big data … especially coming from Trump …. but it reminded me of an opinion piece that Peggy Noonan wrote in the WSJ soon after Obama’s 2012 election win.
Noonan had a riff about predictive analytics that caught my eye.
It pointed out one of the downsides of predictive analytics … the craft of crunching big data bases to ID people, their behaviors and their hot buttons.
Here’s what Noonan had to say …
In the days after the 2012 election the Democrats bragged about their technological genius and how it turned the election.
They told the world about what they’d done—the data mining, the social networking, that allowed them to zero in on Mrs. Humperdink in Ward 5 and get her to the polls.
It was quite impressive and changed national politics forever.
In 2008 Mr. Obama won by 9.5 million votes. Four years later, with all the whizbang and money, he won by less than five million.
When people talk about 2012 they don’t say the president won because the American people endorsed his wonderful leadership.
They say he won because his team outcomputerized the laggard Republicans.
This has left him and his people looking more like cold technocrats who know how to campaign than leaders who know how to govern.
And it has diminished claims of a popular mandate.
Predictive analytics certainly won the battle.
Noonan raised an interesting question: did it win the war?
I think there’s a broader message in there for us number crunchers.
A lesson that Trump may have internalized and activated.
If you’re largely indistinguishable from the competition, you need to win battles at the margin.
You know, locate each and every persuadable person and drag them to the polls.
But if you have a stand-out personality, a “sea-change” set of ideas and a bold aspirational theme … maybe you don’t need to worry about eeking out votes at the margin.
Obama did it in 2008 with “Hope & Change” aimed a Bush-haters, safety-netters and identity-inspired voters.
Trump has “Make America Great Again” aimed at the 100 million folks who are “working scared”.
See the similarity?