I'm interested in doing segmentation/clustering of users in clickstream data and am looking for some good suggestions about how to go about it.
Lets say my data consists of observations made up of visitors to a website. The data is in clickstream/weblog format and so is made up of users cookie data. Lets say I can identify unique users via their IP address (as a basic example). How should I go about preparing my data so that it can be segmented to find users with similar behaviours? One of my thoughts around this, is that because the data is event-driven, the same user can obviously appear multiple times in the data even though it may all be related to the same session of that user. How are these types of problems tackled so that you can perform segmentation based on user behaviour?
Thanks for your suggestions!