Capturing marketing events and data models

A selection method, comprising:

• providing a database system comprising a database manager software application stored on a computer readable medium, a first database structure storing a first list of candidates, a second database structure storing a plurality of data models, and a third database structure storing a second list identifying marketing events and a third list of calculated value scores associated with the marketing events, wherein said database manager software application comprises a retrieving tool, a computing tool, an optimization tool, and an application tool, wherein each marketing event from said second list comprises a marketing offer and an identified channel means for communicating said marketing offer, and wherein said value scores are associated with an expected profit gain associated with each said marketing offer;
• retrieving by said retrieving tool, at least one data model from said data models in said second database structure;
• applying by said application tool, said at least one data model to at least one candidate from said first list of candidates with respect to a first marketing event from said second list;
• applying, by said optimization tool, constraint data to said marketing events, wherein said constraint data comprises first data and second data, wherein said first data consists of an amount of money regarding execution costs for offering said marketing events to said at least one candidate, wherein said second data consists of budgetary data regarding a total budgeted amount allotted for offering all of said marketing events, and wherein said execution costs comprise costs for promotional materials, mailing costs, and telemarketing costs;
• receiving, by said computing device, timing constraints associated with offering successive marketing events comprising a same type of marketing offer;
• first determining, by said optimization tool in response to said receiving said timing constraints, that said first marketing event of said marketing events comprises a same type of marketing offer as a marketing offer comprised by a second marketing event of said marketing events;
• second determining, by said optimization tool in response to said receiving said timing constraints, that a timing conflict exists between offering said first marketing event and offering said second marketing event;
• eliminating, by said optimization tool from said second list in response to said first determining and said second determining, said first marketing event;
• computing, by said computing tool, response probability scores for said marketing events and all of said candidates, wherein each of said response probability scores are computed using said at least one data model;
• and
• computing by said computing tool, a ranking score for each of said marketing events for all of said candidates, wherein each of said ranking scores is computed by multiplying a value score from said third list with an associated response probability score of said response probability scores;
• and
• generating, by a computer processor of said database system, a final ranking list comprising each of said marketing events in a specified order associated with said ranking scores, wherein said final ranking list does not comprise said first marketing event.

A computer-executable program product comprising computer executable instructions tangibly embodied on a computer readable medium that when executed by said computer perform the method steps comprising an algorithm adapted to implement a selection method within a database system, said database system comprising a database manager software application stored on a computer readable medium, a first database structure storing a first list of candidates, a second database structure storing a plurality of data models, and a third database structure storing a second list identifying marketing events and a third list of value scores associated with the marketing events, wherein said database manager software application comprises a retrieving tool, a computing tool, an optimization tool, and an application tool, wherein each marketing event from said second list comprises a marketing offer and an identified channel means for communicating said marketing offer, and wherein said value scores are associated with an expected profit gain associated with each said marketing offer, said method comprising the steps of:

• retrieving by said retrieving tool, at least one data model from said data models in said second database structure;
• applying by said application tool, said at least one data model to at least one candidate from said first list of candidates with respect to a first marketing event from said second list;
• applying, by said optimization tool, constraint data to said marketing events, wherein said constraint data comprises first data and second data, wherein said first data consists of an amount of money regarding execution costs for offering said marketing events to said at least one candidate, wherein said second data consists of budgetary data regarding a total budgeted amount allotted for offering all of said marketing events, and wherein said execution costs comprise costs for promotional materials, mailing costs, and telemarketing costs;
• receiving, by said computing device, timing constraints associated with offering successive marketing events comprising a same type of marketing offer;
• first determining, by said optimization tool in response to said receiving said timing constraints, that said first marketing event of said marketing events comprises a same type of marketing offer as a marketing offer comprised by a second marketing event of said marketing events;
• second determining, by said optimization tool in response to said receiving said timing constraints, that a timing conflict exists between offering said first marketing event and offering said second marketing event;
• eliminating, by said optimization tool from said second list in response to said first determining and said second determining, said first marketing event;
• computing, by said computing tool, response probability scores for said marketing events and all of said candidates, wherein each of said response probability scores are computed using said at least one data model;
• and
• computing by said computing tool, a ranking score for each of said marketing events for all of said candidates, wherein each of said ranking scores is computed by multiplying a value score from said third list with an associated response probability score of said response probability scores;
• and
• generating, by a computer processor of said database system, a final ranking list comprising each of said marketing events in a specified order associated with said ranking scores, wherein said final ranking list does not comprise said first marketing event.