I'm interested in identifying events (patterns) that occur before an event of interest.
For example, a customer calls in to complain or a customer checks their balance online then the customer closes the account (event of interest). Data is in a form of a sequence of events with a time stamp.
I would like to know what methodologies (and software) people are using for such a task.
I'm open to exact patterns (sequence of events), frequency of events (calls in multiple times to complain), and timing of events (80% of event A leads directly to event of interest within X days). Basically, open to any approach people are using to identify patterns leading up to an event.
Thus far I found the
CSPADE algorithm as available in the
arulesSequences package in R. It seems to be able to identify sequence of patterns and which items co-occur. However, I don't think one can set a target event for it to find a pattern.
I'm open to algorithms available in R, Python, or SAS.
Thanks so much!