Birds of a feather, flock together. So do voters.
Find areas with high densities of likely voters with cluster analysis to canvass smarter – not harder.
How do you reach the most potential supporters, in the least time and money with few volunteers? Focus on areas with high densities of likely voters so your canvassers spend less time traveling. How do you find these voter clusters when working with files with millions of voter records spanning dozens of counties or an entire state? Use cluster analysis to canvass smarter. It’s a fast, easy and affordable.
Voters with different political beliefs are spread out in a voting districts, but they also tend to congregate in specific areas. As the saying goes; “Birds of a feather, flock together.” This blog describes how grassroots organizing groups in Florida are using cluster analysis to find the most promising areas to canvass. In choosing party affiliation as the clustering criteria in the software, they can:
- Analyze the Voter File and first map all the voters in a chosen area quickly
- The app calculates where the most voters with that criteria live close to each other
- Display the high-density clusters along with the count of the voters in the cluster
- These insights are then used to refine their canvassing strategy
Canvass smarter with cluster analysis
A cluster is a collection of people who are similar to others within the same cluster. Business marketers use cluster analysis to focus their efforts on areas where they are most likely to get better results. A few of the commercial applications of cluster analysis include:
- Marketers discover distinct groups in their customer bases, and use this knowledge to develop targeted marketing programs
- Insurance Companies identify groups of motor insurance policy holders with a high or low average claim cost
- Real-estate Brokers identify groups of houses according to their house type, value, and geographical location.
The same approach works just as well for political canvassing. Clustering analysis is a great tool to focus your canvassing activities to achieve better results.
How to apply Cluster Analysis to canvassing
The canvassing planners uploaded the voter file with the attributes such as party affiliation, age, race, gender into the app. They then chose the symbols to represent the clusters and which attribute they wanted to cluster around. In this project they chose party affiliation. They also defined the cluster radius which is how big an area they wanted to consider. In an urban area with tightly packed buildings, the cluster radius would be smaller than a rural area where people live further apart. The software then produces the map above in a few minutes with the high density clusters of likely voters. (A special thanks to Orhun and Olga for help with this project).
TakeAway: Canvass smarter, not harder.
Reposted from Democracy Labs with permission.
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