Cluster personas with 80% or more similar attributes -using the K-means algorithm. Therefore create targeted groups of personas of nearest neighbors: K-means is a centroid-based clustering algorithm, where we calculate the distance between each data point and a centroid to assign it to a cluster. The goal is to identify the K number of groups in the dataset.

The above requires an import of current lead datasets where those leads will be matched with persons you created- so you are actually able to cluster your actual contacts database within specific persona clusters pre-created - using the KMeans algorithm with a nearest-neighbor approach.