I am trying to build a propensity to pay model given an intervention to a customer.
- The population I am dealing with are customers who were supposed to pay some amount on a certain date but have not paid.
- such customers are contacted via Call centres to remind them of the payment to be made
- some customers pay, some don't Problem statement: Build a propensity to pay scores for these customers. My current approach:
- data: calls made via call centre on a certain month
- if a customer has made a payment within 6 days of intervention, tag them as 1, else 0
- considered few demographic features as well as few operational metrics those may be correlated to a customer Making a payment
- build a classification model (maybe logistic regression) to get the propensity scores.
- does the approach mentioned make sense
- what is the need of propensity scores matching
- the data is not experimental, its observational, can I use the target variable with tag 1, mentioned earlier as a test group and tag 0 as the control group.
Any input on this will be very helpful. Thanks in advance!