What I did
- Code:
React.js, Mapbox, D3 - Database:
PostgreSQL
Project Goals
This project is granted by Lousiana State University Research & Technology Foundation under LIFT² Fund The LSU LIFT² Fund was created by LSU Board of Supervisors in January of 2014 to help “Leverage Innovation for Technology Transfer” across all of the campuses of the LSU system.
Cedar Analytics optimized micro-targeting efforts for political advertising campaigns through geographical population analysis tools.
Methods and Approaches
Real-time input from polling data, data from ground-based canvassing efforts, voter files and voting histories were used to develop an algorithm which generated individual voter scores. These scores were then visually represented through a map-and-chart system for geographical analysis.
Results
The algorithm optimized micro-targeting efforts for Bill Cassidy’s Louisiana State Senate Race (2014) by identifying specific population groups necessary for his advertising campaign to micro-target. The algorithm was 99% accurate in comparison to the election results.
Conclusion
Based on the 2014 Louisiana State Senate Race, Cedar Analytics was successful in optimizing micro-targeting efforts for a political advertising campaign through geographical population analysis tools.