I am working on a segmentation model that has been fed into the company by an external agency which created the segmentation based on surveys. I have a number of 6 attitudinal segments and after ascribing them to our database via proxy variables, I wish to test if it makes sense from a statistical point of view to further split (or combine for that matter) the segments.
What kind of methods should I consider applying to tackle this? I have limited experience with clustering (k-means), and not so much from a statistical point of view, but more from a perspective where I'd only care about measures of predictive accuracy and not so much about exploratory modelling, so any directions would be helpful.
P.S. The original segmentation will have to stay unchanged (business requirements...)