K-means cluster analysis is a tool designed to assign cases to a fixed number of groups (clusters) whose characteristics are not yet known but are based on a set of specified variables. It is most useful when you want to classify a large number (thousands) of cases.

A good cluster analysis is:

- Efficient. Uses as few clusters as possible.
- Effective. Captures all statistically and commercially important clusters. For example, a cluster with five customers may be statistically different but not very profitable.