Self-Organizing Maps (SOMs)
The SOM is a type of neural network that was originally developed for data visualization, where the objective is to reduce data from a high number of dimensions (attributes) down to two so they can be seen on a map.
The process of reducing the dimensionality of the data also results in grouping based on similarities of the observations. Essentially this means that SOMs segment data when they reduce the dimensionality of the data. Through tests in various industries we have found that segments created by this process are very attractive and actionable and often superior to segments formed by more conventional methods like cluster analysis. SOMs fall under a category called unsupervised neural networks.