Complex event processing for context-based digital presentations

A system comprising:

• a memory configured to store operations;
• and
• one or more processing devices configured to process the operations, the operations comprising:
• receiving, from a data repository, one or more raw data streams of real time data in response to a query transmitted to the data repository from a data stream consumer application running on a server, the query requesting predetermined real-time data associated with an end user,
• determining an identity of the end user based on the one or more raw data streams,
• filtering, using contextual filtering parameters, the received one or more raw data streams to produce filtered data,
• applying a set of rules correlating the filtered one or more raw data streams with incentive programs relevant to the filtered data to generate correlated data,
• querying the data repository for historical data associated with the end user based on the determined identity of the end user, the historical data being data captured within a predetermined time window prior to a capture time of data in the one or more raw data streams,
• calculating a propensity score of the end user based on the received historical data,
• ranking the correlated data based on the propensity score, and
• sending a notification to an end user device, the notification including one or more incentives based on the correlated data ranking.

A non-transitory computer-readable medium storing instructions that when executed by one or more processors of a server transmitting notifications to an end user, cause the one or more processors to:

• receive, from a data repository, one or more raw data streams of real time data in response to a query transmitted to the data repository from a data stream consumer application running on the server, the query requesting predetermined real-time data associated with the end user,
• determine an identity of the end user based on the one or more raw data streams,
• filter, using contextual filtering parameters, the received one or more raw data streams to produce filtered data,
• apply a set of rules correlating the filtered one or more raw data streams with incentive programs relevant to the filtered data to generate correlated data,
• query the data repository for historical data associated with the end user based on the determined identity of the end user, the historical data being data captured within a predetermined time window prior to a capture time of data in the one or more raw data streams,
• calculate a propensity score of the end user based on the received historical data,
• rank the correlated data based on the propensity score, and
• send a notification to an end user device, the notification including one or more incentives based on the correlated data ranking.