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How did the polls get it wrong?

November 9th, 2016 will go down in history as the day the United States of America elected Mr. Donald J….

November 9th, 2016 will go down in history as the day the United States of America elected Mr. Donald J. Trump, which, needless to say, came as a surprise to many people, especially pollsters. During the past weeks, there has been quite a few finger pointing towards the polls. Many are wondering, how did the polls get this so wrong?

We decided to have a little chat with our Head of Research, Henrik Nielsen, so he could shed light on this matter.

This is not the first time polls have gotten it wrong, right?

Have you ever heard of the Shy Tory Factor? It refers to the British general elections of 1992 and 2015, when the Conservative Party, aka the Tories, significantly proved the polls wrong. In both elections, polls didn’t take into account conservative voters that hid their support for the Conservative Party.

Last year, Danish parliament election polls also got it wrong, none of them predicted the rise of The Danish People’s Party. Just this summer, we were all witnesses to Brexit even though all the polls predicted a win for remain.

Does this mean that we’re going to stop using polls to predict elections, among other things?

Many political experts, who got this election completely wrong, have already started to proclaim that this marks the end of polling and are calling polls a wild goose chase. We should take this with a grain of salt since they are trying to protect their own brand as political experts. In other words, no, this is not the end of polling. Polls attract readers, viewers, and clicks, which in turn brings in advertising money and as Liza Minelli says, money makes the world go around.

It’s not the end of polling but should it be?

Polls are not a wild goose chase, even though many are calling them that. Polls are useful and render excellent data; however, pollsters need to start re-examining the methods used in polling. Just like in 1992 Britain, before the 2016 US election, experts already started dismissing “shy trump” supporters. They based this dismissal on pre-election polls – ironic, right?

Back to your original question, pollsters need to increase their efforts and revise the way they do things and the rest of us need to remember that, even if the evidence says otherwise, polling carries uncertainty.

What should pollsters do in the future?

The French presidential election is coming up in the spring of 2017, so all of us, especially pollsters, need to look out for the “Shy Trump” phenomenon. As I said before, looking at polls is not a wild goose chase but, as in all aspects of life, polls have to be done according to the 7 P’s – Proper Preparation and Planning Prevents Piss Poor Performance.

The future of polling requires that pollsters find a way to handle the “Shy Trump” phenomenon. I will be following, and suggest everyone does, the polls on the French presidential election and see if the pollsters are able to figure out a way to handle the “Shy Trump” phenomenon or whether Marie Le Pen and the National Front will get a much better result than the polls predict…

The poll we conducted about the US election showed that 83.1% would’ve voted for Hillary Clinton, did we also get it wrong?

Ha! First things first, our poll is not representative, that being said it did show something interesting. It suggested that the majority of respondents would rather enjoy a beer in the company of Mr. Trump than Mrs. Clinton.

This question serves as a proxy for the winner of the election since it turned out to be a better forecast of the US election result than 99% of polls used the media coverage.


Are you saying Enalyzer saw it coming?

No, not at all but it’s still funny. Also, wouldn’t you rather admit to a beer than to a vote for the US presidency?

Did anyone see it coming?

Yes, there was, in fact, one poll that foresaw the victory of Mr. Donald Trump, however, this poll was written off as nonsense by the majority of the high esteemed panel of political experts, you know, those experts who got it all wrong.

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