1. A computer implemented method, comprising: in a set of customer records containing first transaction data for plural customers, correlating, using a correlating computer system comprising a digital computer comprising a central processing unit, memory, an input device, and an output device, transactions in a first set of input classes that occurred in a first time period to transactions in a first correlated class that occurred in a second time period, wherein the second time period is subsequent to said first time period, thereby defining first input class correlation data for said first set of input classes, wherein each datum of said first input class correlation data represents a statistical correlation between the existence of transactions that occurred in at least one transaction class in said first set of input classes in said first time period with transactions that occurred in said first correlated class in said second time period; and deciding whether to issue a transaction incentive to a customer based at least in part upon (1) first CID transaction data, said first CID transaction data specifying data for transactions that are associated with a first CID for said customer and (2) said first input class correlation data for said first set of input classes; wherein said deciding comprises a deciding computer system storing in memory a predictive model function defined at least in part by at least one datum of said first input class correlation data, storing in memory said first CID transaction data, and said deciding computer system applying said predictive model function to said first CID transaction data, thereby resulting in first CID correlated class predictive data; and wherein said correlating computer system and said deciding computer system may be the same or different computer systems.