Any business managers still skeptical about the power of analytics should keep their mouths shut following this week's election. The Presidential race was a demonstration of the power of analytics over gut instinct and experience.
According to Time.com, President Barack Obama's campaign relied on analytics and techniques that will be familiar to smart businesses.
[F]rom the beginning, campaign manager Jim Messina had promised a totally different, metric-driven kind of campaign in which politics was the goal but political instincts might not be the means. "We are going to measure every single thing in this campaign," he said after taking the job. He hired an analytics department five times as large as that of the 2008 operation, with an official "chief scientist" for the Chicago headquarters named Rayid Ghani, who in a previous life crunched huge data sets to, among other things, maximize the efficiency of supermarket sales promotions.
While Obama's team won praise in 2008 for its "high-tech wizardry," it suffered from a proliferation of databases. Volunteers making phone calls through the Obama Website worked with different lists than callers in the campaign offices. Get-out-the-vote lists and fundraising lists were different. Businesses face these issues all the time, as sales lists for different business units differ from each other, as well as from CRM systems.
For the first 18 months of the re-election drive, the campaign started from scratch with a single, massive database, capable of merging information from pollsters, fundraisers, field workers, consumer databases, social media, mobile contacts, and the main Democratic voter files in swing states.
How did the campaign use that data?
To predict what kinds of people would be persuaded by what kinds of appeals. "Call lists in field offices, for instance, didn't just list names and numbers; they also ranked names in order of their persuadability, with the campaign's most important priorities first."
The campaign discovered that people who had unsubscribed from 2008 campaign email lists were susceptible to being pulled back into the campaign. Marketers call this technique "retargeting."
For example, if a consumer puts an item in their shopping cart but decides not to buy it, marketing automation software will fire off an email to the consumer the next day to attempt to nudge the consumer to buy, perhaps with a special discount offer. It works for selling pants online, and it turns out to work for electing a president, too.
Strategists tested scripts for different demographic groups, and whether a call from a local volunteer would perform better than someone from a non-swing state, like California.
The new database allowed the campaign to beat fundraising goals as well.
The campaign also used sophisticated online marketing techniques, targeting ads based on individual behavior that was tracked with cookies, said the Wall Street Journal. "A wealthy urban liberal sees different ads online than a working-class centrist. People who care more about jobs see different ads than people who focus on social issues."
But the most visible way that metrics won the 2012 election was in predicting the winner. While TV pundits used their long experience and gut feelings to say the election was too close to call, or even predicting a Romney landslide; statistician Nate Silver, writing at the New York Times blog FiveThirtyEight, called the election with staggering accuracy.
Just predicting that Obama would win wasn't particularly interesting. After all, a coin-toss can predict the winner half the time in a two-person race. No, Silver's analytics predicted the outcome in 49 of the 50 states (Florida still hasn't weighed in as I write this late Wednesday), and got the margin of victory right within a half percentage point. (Silver predicted 50.8 percent Obama and 48.3 percent Romney. The reality as of Wednesday was 50.4 percent Obama to 48.1 percent Romney.) See for yourself:
And Silver wasn't alone. Several other statisticians made similarly accurate predictions. Silver, in particular, was widely derided by political pundits before the election, but now he's getting the last laugh as he called the election right, and the pundits got it wrong.
I would love to know all the variables Nate Silver used in his preditiions I believe his breed of analytics will drive many elections for years to come
It's a remarkable result, but I admit I can't see how those electoral college numbers add up either. I thought every state was winner-take-all -- it turns out Nebraska and Maine aren't, but that doesn't really solve the conundrum.
I am exited that Knowledge through analytics is able to better help us make decisions on what may happen. Of course having a background in IT is the reason I am happy analytics is beginning to show the way.
I'm seeing reports that Florida has gone to Obama. The Huffington Post calls it that way. The New York Times still shows the count as not done, with Obama leading.
If the HuffPo is right, that'll make Silver 50 for 50. However, the final electoral tally would be 332 votes for Obama, compared with Silver's predicted 313. I suspect the difference is because of some states giving part of their electoral votes to one candidate and part to another, but I'm not sufficiently familiar with election mechanics to be sure.
It's a powerful illustration of the power of analytics.
There is indeed some long term significance to all this, if 2008 and 2012 are any guide. If it becomes possible to know, with some accuracy, the outcome of the election well in advance of Election Day, what do the campaigns do? Concentrate on turnout, I suggest.
The number of undecideds in US Presidential elections now seems so small, that one wonders whether the vast expenditure is worth it, in an attempt to change a few, unpredictable votes.
And what will the media do, if the "horse race" is a foregone conclusion?
Personally, I was fed-up with all the polls and predictions long before the real results were created. And part of me is sad that we can predict human behavior like this, even in the voting booth. The other part of me is amazed -- and I'd be astounded at any company that doesn't invest in analytics and big data. It should be just as much a part of SOP as email and spreadsheets, given the incredible results we're seeing from so many disparate disciplines and industries.
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Edmunds separates customers into segments based on the info it collects on its site and from partners, and uses that to push out custom content, said Brian Baron, director of business analytics for Edmunds.com, at Predictive Analytics Innovation Summit.
The automotive website uses propensity modeling to target ads and customer registration forms, said Brian Baron, director of business analytics for Edmunds.com, at Predictive Analytics Innovation Summit.
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