This 2016 presidential electoral app attempts to predict the winning candidate within a micro demographic area leveraging statistical models from seven different data sources. In addition, the app also reveals sentiment differences by age, education, gender and race.
What Can Presidential Campaign Teams Teach Organizations About Analytics?
The success of presidential electoral campaign teams is becoming increasingly grounded in the evolutionary adoption of analytics. Similarly, enterprises large and small are well suited to follow the analytic lessons that can be learned from these teams.
Examining Trends in Political Partisanship across US Counties and Time
Examining and visualizing partisan preference changes within the individual counties of each state in the US from post-World War II era up through the present set the stage for understanding political cultural shifts taking place on a hyperlocal level.
Partisanship Extremes: Factors Driving Political Leanings at the Local Level (3 Part Series)
By analyzing patterns of voter preferences by location, age, family status, religion and other demographic indicators, this three part series takes an analytical view to determine how political preferences may be influenced by these attributes.
Presidential Election App Architecture Explained
Learn how the Decision 2016 Presidential Election app used the Alteryx Analytics Platform to predict the winning candidate within a micro demographic area.
The Models Behind the Predictions: Building of the Presidential Election App
What data was used, how that data was used, and which models were tested in order to develop the 2016 Presidential Election App? Take a peek behind our 2016 Presidential Election App to learn what models were used to produce the predictive outputs.