Media Exposure - What Election Polls Missed

By Todd Murphy, Vice President, Universal Information ServicesMonday morning quarterbacking is the easiest job in the world, especially if you have data analysts like I do at Universal Information Services. With the Trump v. Clinton Presidential election in the rear view mirror by a week, it appears obvious why Donald Trump won over Hillary Clinton. Don’t worry, I’m not going to go anywhere near the politics of this issue, but only point out why media placement, message points, and share of voice media exposure is at least a better indicator of a future outcome than polling.

Past Performance Can Indicate Future Outcomes

At Universal Information Services we’ve been using media exposure as a predictor of outcomes since the Obama vs. Romney race. What we have found is that unless there is some extraordinary circumstance that causes the media exposure for one candidate to eclipse the other, there appears to be a strong correlation between media exposure and an election outcome. An extraordinary media event would be something so scandalous as to essentially render the candidates opportunity impossible.Yes, the 2016 Presidential Election was extraordinary, in fact, I would argue unprecedented. However, both candidates had an approximately equal number of detracting message points to effectively balance the playing field. In other words, neither candidate was able to shoot themselves in the foot so badly they couldn’t recover. Frankly, short of killing someone on stage at a debate, I’m not quite sure what issues would have hindered either of them.

What Can Share of Voice Tell Us?

Although Universal Information Services provides deep analysis of news and media exposure, this post is looking at only a few relatively simple measures. Our PR measurement tools let us generate a comparison of media exposure between two or more subjects. In this case, we retroactively analyzed the volume and type of coverage both Presidential candidates, Clinton and Trump, received in the 30 days leading up to the election on November 8th. What was revealed was that Trump was receiving more media exposure, across all media types, for that period. And although some call share-of-voice a vanity metric, the impact from message quantity does factor in to the overall potential for behavioral change. The more one is exposed to a message the greater the probability of that message affecting behavior. How much message volume impacts behavior requires a deeper dive, but this is one small piece of evidence pointing towards a Trump victory.

Why Does the Type of Media Outlet Matter?

Quality of a media outlet, credibility, viewership/impressions, and ease of amplification are several factors that determine the velocity a message might gain through placement in one type of outlet over another. For example, a live interview on Fox News television reaches millions of viewers. The link to that story also has the potential to reach millions of people because of the committed viewer base that Fox News has. In tandem, a single story on Fox News and their website could travel wider and impact more people than a blog post might from a political website in Iowa. This is not a reflection of the quality of the information contained within this story, but rather the magnitude a media outlet can impact the public. More stories on the more prevalent, higher rated outlets, the greater the probability a message has of impacting a voter. Here we see Donald Trump surpass Hillary Clinton in each of the five measured types of media outlets. Another piece of the pie pointing to a Trump victory.

How Can News Aggregation Platforms Help?

Analyzing the volume of messages accumulating within broad media platforms, or points of aggregation, can easily be used to validate the above measure of media type value. In the above chart we looked at five platforms that pull stories and content from a variety of sources. Again, we see that Trump, in green, surpasses Clinton on all five platforms. Here we are simply using the diversity of an aggregation platform to validate what the data is telling us from other measures. Accurately spotting trends, knowing how to normalize disparate data, and having professional analysts to render valid insight are just a few things a reliable media measurement service can do when analyzing media messages. In the case of the Trump v. Clinton surprise, it becomes clearer that maybe the Trump victory was no surprise at all.As mentioned at the beginning of this post, we’ve studied the predictive qualities monitored media results can have. We’ve seen media measurement more accurately predict the outcomes of a race than polling can. The 2016 presidential election was different for us. When you look at a candidates messaging, and their ability to impact behavior, it may be easiest to think of it in terms of energy. From a physics perspective, the potential to retain or release the energy of their message is arguably equal in both candidates at the beginning of a race. When you add the media as a message catalyst, that internal energy, enthalpy (H),  the equilibrium of the two candidates can change and affect the impact of one candidate over another. It is not uncommon for us to use physics when analyzing message impact.But as you know, presidential candidates, especially this cycle, are not a static thermodynamic system. Although there is much hot air in each (sorry, editorial comment), I’m sure nobody would argue that either candidate were analogous to “ideal gases”. Science aside, how do you explain the gulf between the expectation of the presidential outcome and the actual outcome? All the analysts are looking closely at this race, so every theory is interesting. Please share your theories.