To gain a deeper insight into where the public stands, we decided to ask them. The wording of questions on topics like climate change can often have a heavy influence on the results, and we attempted to keep it as neutral as possible. Our panelists were asked to allocated between warming temperatures being driven by human activities, and natural changes. The exact wording was: “When thinking about warming temperatures on our planet, what percent do you believe is due to human activities and what percent do you believe is due to natural changes?”
The amount of information and content that the average consumer receives online and on our phones today dwarfs previous generations—and you’d be hard pressed to find any marketing expert that anticipates this trend abating.
In fact, it was estimated that about $107 billion was spent in America alone in 2018 on digital advertising. For campaigns last cycle, that amount is estimated to be between $900 million and $1.8 billion. This is clearly a big range. But it’s a tough number to pin down based on the way expenditures are reported. For comparison, in 2014 digital spending was estimated at about $250 million.
The challenge in the political world is how to measure what’s being done and the effectiveness of that effort. Digital consultants have their metrics such as impressions, clicks, et cetera. But are there other ways to understand the reach and effects of the money being spent?
We have been tracking opinions over the course of Kavanaugh’s rocky journey to the Supreme Court. Through Trendency, an online research platform that gathers responses from representative panels of registered voters across the country, we have amassed a longitudinal dataset that allows us to detect small movements and changes in opinion over time as different events occur. One of the ways that our data is different from traditional research is that we do not force our respondents into a yes or no question set, but allow them to indicated how much they support both of these positions.
By now we all know the adage, modern data analysis is like drinking from a firehose. However, we might argue it’s more like standing under a waterfall. Through the data we collect is abundant, our human capacity to take it in and analyze it is limited. Given the abundance of data, it is increasingly difficult to tell where to look to find interesting insights and useful analysis. While this challenge is one that is likely to continue to grow exponentially, many of us are trying to develop tools to help tackle this problem. Our newest: volatility scores.