Election Data Proved A Big-League Failure

The day after the big presidential upset data was difficult to find. Now, think about the next election and what predicative data you’ll be seeing on TV news network.

How did the polls get it so wrong?

To be fair, Nate Silver of was leery about some of the last polls, just days before the election -- especially when Clinton’s numbers narrowed to a 2.5 to 3.5 point lead, within the range of error.

Still, in the days before that -- the week leading up to the election -- many, including Silver, had posted daily predictive missives, giving Clinton a big chance of winning. Early on November 8, FiveThirtyEight gave Clinton a 71.4% chance of winning when culling all polling data.

Perhaps one bit of polling information that would have been good to get was that of Cambridge Analytica, the President-elect Trump data team.

Matt Oczkowski, director of product for the company, told, he noticed a decrease in black turnout, an increase in Hispanic turnout, and an increase in turnout among those over 55.



Additionally, there was overwhelming turnout of voters in rural areas -- especially in Ohio, Michigan, Iowa and Wisconsin.

Oczkowski said: “The amount of disenfranchised voters who came out to vote in rural America has been significant.” He added:  “This is not something that political intuition would tell you, but our models predicted most of these states correctly.”

Why didn’t other polls have that? Because polling samples were very incorrect, especially among “likely voters.”

Welcome to the new world of big data for elections, stuff that, on the whole, wasn’t at all that predictive. Even Trump wasn’t all that convinced that big data was needed for his campaign -- only hiring Cambridge Analytica late in the campaign in the summer.

If you were were a brand manager of a particular product/service that failed to sell with this kind of data, you would ask yourself: Why -- in the age of  ever expanding information -- did my big data resources fail?

And if you are a TV news network looking at the next election, what important and valuable election poll content will you use in future?

3 comments about "Election Data Proved A Big-League Failure ".
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  1. Bob Gordon from The Auto Channel, November 10, 2016 at 11:34 a.m.

    Big Data Without Humanity Is Bull Shit

  2. Robin Hafitz from open mind strategy, November 10, 2016 at 11:53 a.m.

    The polls were wrong.  Does that mean marketers should see research as "broken"?  Hardly.  Trump won the states that took him over the top (Wisconsin, Pennsylvania) by 0.9% and 1%. Clinton won the popular vote by 0.2%. That is how close voting Republicans and Democrates are in numbers in our gerrymandered nation, which makes polling data highly unstable.  By contrast, marketing contests are not winner-take-all battles between two competitors, and research to aid marketers is generally useful, even if "off" by a single percentage point.  But, as this article points out, what pollsters missed was the level of fervor of white ex-urban voters, and that their turnout would trump the turnout of other groups.  Brian Williams suggested on election night that they should have counted the lawn signs.  After all, putting a name in your front yard is a good indication of avidity.  On this point, marketers should take note: in addition to conducting survey research, they should make sure to get out and connect with people individually, where they live, to get a more informed sense of what's going on and how it will affect them.

  3. Paula Lynn from Who Else Unlimited, November 10, 2016 at 8:16 p.m.

    Who profited from all the 25 million daily polls ? I polled people to get that number. Wrong questions ?

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