Since the turn of the century, segmented data has been used more and more effectively in both business and politics. Segmentation is commonly broken down into Demographic, Behavioral and Attitudinal data. Up until recently, most segmentation has been limited to Demographic and Behavioral. But beginning in 2008, candidate Barack Obama began to enlist the support of Silicon Valley to move into the Attitudinal segment, and continued through his presidency. In fact, the Bernie Sanders phenomenon in the 2016 election was as much due to his extensive use of attitudinal data as it was to a national swing toward socialism. It is this SAME Attitudinal data that Asymmetrical Political Solutions, LLC has to offer to its clients, and it offers the same unexpected results.
What both the media and the general public don't understand is that Donald Trump didn't win the election with outlandish tweets alone, nor did he win the election with "attack nicknames" alone, nor really did he win it with issues like building the border wall alone. In fact, his Campaign Manager Kellyanne Conway, a sophisticated pollster and political operative, delved into the Attitudinal Segment like no Republican campaign did before her.
By coupling oft used Demographic and Behavioral data with more cutting edge Attitudinal data, the Trump campaign was able to capture important segments of the voter population in the swing states, thus securing a victory in the Electoral College. Whether you love President Trump, hate President Trump or are indifferent to President Trump (said no one ever, or so it seems), a smart political operative will look at the advent of Attitudinal Data that marked this campaign.
Like Asymmetrical Political Solutions, LLC, Kellyanne Conway's first choice of data vendors was L2. Coupled with their more classic "VoterMapping" tool is available HaystaqDNA, a plethora of Attitudinal data. This brings the quality, breadth and sophistication of L2 data to the forefront, and gives Asymmetrical Political Solutions its edge...The Attitudinal Edge.