I have a bunch of customer profiles stored in a elasticsearch cluster. These profiles are now used for creation of target groups for our email subscriptions.
Target groups are now formed manually using elasticsearch faceted search capabilities (like get all male customers of age 23 with one car and 3 children).
How could I search for interesting groups automatically - using data science, machine learning, clustering or something else?
r programming language seems to be a good tool for this task, but I can't form a methodology of such group search. One solution is to somehow find the largest clusters of customers and use them as target groups, so the question is:
How can I automatically choose largest clusters of similar customers (similar by parameters that I don't know at this moment)?
For example: my program will connect to elasticsearch, offload customer data to CSV and using R language script will find that large portion of customers are male with no children and another large portion of customers have a car and their eye color is brown.