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September 11, 2014

Create “true” cluster samples with L2 DataMapping

Utilizing a new mathematical model and L2 DataMapping’s industry leading high-speed data visualization, you no longer need to second guess your cluster sample data.  

Most vendors are using street or precinct sorting of voter data prior to creating the clusters.   The problem with this geographical sorting is that when extra records are needed to complete a cluster, boundary lines can be crossed resulting in records from a single cluster being separated by miles.  This wide geographic split defeats the entire purpose of a cluster sample.

Seeing is believing… 

L2 DataMapping identifies the first sample point on the map and then geographically ‘spirals’ outward, filling out the cluster with qualifying records.   And while we know you can trust this data, don’t take our word for it; see your selected cluster points on a street map.


(Two cluster samples up close with 100 records per cluster)

(Two cluster samples up close with 100 records per cluster)


(A wider view showing ‘clusters’ of 100 records per cluster)

(A wider view showing ‘clusters’ of 100 records per cluster)


The cluster sample export files will contain unique numbers for each cluster.  That unique number will appear in a cluster-sorted file with the record for each voter bearing that cluster number.

By working with L2 DataMapping you’re ensuring your campaign or client will have the highest quality voter data along with the only true cluster sample.

For more information on L2 DataMapping or any L2 product contact Paul Westcott at Paul.Westcott@L2political.com

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