Looking to build a response model (click or no click) on marketing data which displays varying number of offers to a person. I don't want to model which offer they click but do they click any of the offers presented to them. My issue is how to deal with the differing number and types of offers?
Example data could be one table of id's:
id clicked 001 1 002 0 003 1
And varying number of offers per id:
id discount_rate on_amt 001 0.05 100 001 0.10 500 002 0.03 50 003 0.05 100 003 0.10 300 003 0.15 500
Do I create features from the offer data set such as average discount_rate, max on_amt etc.? Or create a very large binary sparse matrix of binned offer types such as rate_5-10_amt_0-50 1/0 and rate_5-10_amt_50-100 1/0 ...?
Or is there a good model that handles variable data like this?