This episode we chat about the methodology behind predicting voter behavior with special guest, Luke Riley who worked in Hillary Clinton’s Brooklyn data operation.
We start by exploring how campaigns and firms like Cambridge Analytica build a predictive mathematical model of the electorate using consumer data and polling.
Then we discuss how this process played out with the dynamics of the 2016 election. Can the best data in the world make up for an enthusiasm gap?
Finally we look forward to the future of campaign data and analytics. What were the lessons learned and where are we headed?
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