I am tasked with performing a clustering exercise for a consumer survey dataset with the hopes of finding distinct consumer segments.
In the past, I've done it using a variety of techniques- hierarchical methods, EM etc. but the dataset has been much smaller with perhaps 12-15 variables.
I've used dimensionality reduction as a starting point and that has helped with smaller number of variables but with over a 100 variables, I'm a little befuddled. The dataset includes mostly numerical but also some categorical data.
How would I go about such an exercise? Distance measures in higher dimensions are tricky and so I'm seeking some guidance here.
A word about the tools of choice- I would like to run it in R but it'll most likely murder my laptop. Any specific database you guys could recommend?
Thanks so much everyone! Appreciate it.