Regarding profiling of products using unsupervised learning

@rumsinha wrote:

I have following data with me:

product which takes character values like"abc", "xyz", etc
Quantity which take numeric values
Amount numeric values
ShipSet count numeric values

I am changing the product to number with as.numeric(product)
then I am performing scale and getting the optimal clusters using silhouette width.
Performing kmeans clusters not giving me good clusters.

how can I improve upon this so that I can have 3 groups of products with high amt/high qty/high shipset, another one with medium and third one with low values?

thanks and regards

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