I have historical transaction information of customers for the last 2 years and other information about the customers like what type of card (gold/platinum) they used for transactions etc. is also there in the dataset. Using this dataset, I will have to forecast the likelihood of each customers transacting next month. What are the different approaches that I can analyze before I choose one?
More info on the problem:
I have customer credit information and transaction history of the cards for an online ticket booking portal. From this portal customers can book flights, cruises and cars. I have to predict the customers who are most likely to book something (flights, cruises and cars) in the next month. Now what possible approaches can I take for this?