The discrimination analysis tells how well descriptive data (generally available for all customers and prospects) will predict segment membership. The confusion matrix shows actual versus predicted segment membership from the discrimination. If all segments are roughly the same size, then there is one chance in n (n= number of segments) for correct classification, if there is no information in the descriptor data; that is, if the classification is done at random So, for a 4 segment solution, a good discrimination should do far better than 1/4 or 25% correct classification. In addition, high values on the diagonal of the confusion matrix indicate good classification.
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