Abstract: This disclosure includes techniques for creating an engagement program forecast. The techniques include receiving customer data and transaction data for a consumer store, the transaction data being at an individual level such that individual customer's individual transactions can be seen in the transaction data. The techniques further include executing, based at least in part on the customer data and the transaction data, a loyalty forecast simulation for an engagement program for the consumer store by utilizing dynamic assumptions and developing an assumption profile for each individual customer. The techniques use the dynamic assumptions and the assumption profiles to develop a forecasted consumer profile for each respective customer over the defined time period and calculate, based at least in part on the forecasted consumer profile for each of the plurality of customers, an engagement program forecast for the engagement program.

Abstract: A system and method for integrating clinical trial data housed in disparate systems. The integration system listens for a clinical trial event broadcasted by any one of the disparate systems. The clinical trial events are the same or similarly defined among the disparate systems. The integration system receives notice of a clinical trial event from one of the disparate systems and then sends a query to the disparate systems requesting metadata corresponding with the clinical trial event. The metadata is comprised of attributes of the clinical trial event and the values of such metadata may differ among the disparate systems. The responsive metadata is stored in an unstructured format and can be displayed in substantially real-time via a graphical user interface.