The customer uses a Kohonen node in an effort to group data into clusters using a self-organizing map of neurons.

The customer uses a TwoStep node to identify the optimal set of clusters within the data.

The customer uses a RFM Aggregate node to identify the optimal set of clusters within the data.

The customer uses a Carma node in an effort to group data into clusters using a self-organizing map of neurons.

Data Audit node

Statistics node

Type node

Report node

Restructure the data and use the new fields as inputs to a time series model.

Move the nodes into a SuperNode to take advantage of the special clustering methods available within SuperNode functionality.

Cluster the data into subgroups to differentiate the campaign's predictions by those subgroups represented within the data.

Transpose the data to use the rows as columns in a new predictive model.