Dynamic selection of groups of outbound marketing events

• US 7,689,454 B2
• Filed: 05/03/2005
• Issued: 03/30/2010
• Est. Priority Date: 05/03/2005
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Selby, David A., Ramsey, Mark S.
• Primary Examiner(s): Bayat; Bradley B
• Assistant Examiner(s): Singh; Gurkanwaljit
• Application Number:
  US11/121,234
• Publication Number:
  US 20060253315A1
• Time in Patent Office: 1,792 Days
• Field of Search: None
• US Class Current: 705/7.33
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

A database system and method for ordering marketing events for offering to candidates. The database system comprises a first database structure storing a first list identifying marketing events, a second database structure storing a second list of candidates, and a database manager software application stored on a computer readable medium. The database manager software application comprises a grouping tool and an optimization tool. The marketing events from the first list are divided into a first plurality of groups. The grouping tool is for dividing candidates from the second list into a second plurality of groups and matching a first group from first plurality of groups with a second group from the second plurality of groups. The optimization tool is for optimizing and sorting the marketing events from the first group for all candidates from the second group.

Claims

1. A database system comprising a computer processor coupled to a computer-readable memory unit, said database system comprising a first database structure storing a first list identifying marketing events and a third list of value scores, a second database structure storing a second list of candidates, a third database structure storing at least one data model, and a database manager software application stored on a computer readable medium, wherein said database manager software application comprises a grouping tool, a computing tool, and an optimization tool, wherein each marketing event from said first list comprises a marketing offer and an identified channel means for communicating said marketing offer, wherein each value score from said third list is associated with a marketing event from said first list, wherein said value scores are associated with an expected profit gain associated with each said marketing offer, and wherein said marketing events from said first list are divided into a first plurality of groups, said memory unit comprising instructions that when executed by the computer processor implements a method comprising:

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 a 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 first list in response to said first determining and said second determining, said first marketing event;

dividing by said grouping tool, candidates from said second list of candidates into a second plurality of groups;

matching by said grouping tool, a first group from said first plurality of groups with a second group from said second plurality of groups, wherein all candidates from said second group comprise a first specified candidate trait;

computing, by said computing tool, response probability scores for said marketing events from said first group for all of said candidates within said second group, 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 from said first group for all of said candidates from said second group, wherein each of said ranking scores are computed by multiplying a value score from said third list with an associated response probability score of said response probability scores;

optimizing, by said computer processor, said marketing events from said first group for all of said candidates from said second group, said computer processor executing said optimization tool to perform said optimizing; and

sorting, by said optimization tool, said marketing events from said first group for all of said candidates from said second group, wherein said marketing events from said first group are optimized and sorted for all of said candidates from said second group by optimizing and sorting said ranking scores for each of said marketing events from said from said first group.

2. The database system of claim 1, wherein said grouping tool is for matching a third group from said first plurality of groups with a fourth group from said second plurality of groups, wherein all candidates from said fourth group comprise a second specified candidate trait, wherein said first specified candidate trait comprises a different candidate trait than said second specified candidate trait, and wherein said optimization tool is for optimizing and sorting, said marketing events from said third group for all candidates from said fourth group.

3. The database system of claim 1, wherein said optimization tool is for generating a priority list comprising said sorted marketing events from said first group, and wherein said priority list prioritizes an order in which to offer each of said marketing events from said first group to all of said candidates from said second group.

4. The selection system of claim 1, wherein said optimization tool is for generating a priority list comprising a first set of marketing events from said sorted marketing events from said first group that fall within a specified set of constraints, and wherein said priority list is for prioritizing an order in which to offer each of said marketing events from said first group to all of said candidates from said second group.

5. The database system of claim 4, wherein said specified set of constraints comprise timing conflicts related to offering all marketing events within said first group.

6. The database system of claim 4, wherein said specified set of constraints comprise budget constraints related to offering all marketing events within said first group.

7. The database system of claim 1, wherein said list of candidates comprises existing customers of an entity that is offering said plurality of marketing events.

8. The database system of claim 1, wherein said marketing events from said first group are sorted and optimized essentially simultaneously.

9. The database system of claim 1, wherein each marketing offer is selected from the group consisting of a product offer and a service offer.

10. The database system of claim 1, wherein each identified channel means is selected from the group consisting of a telephone call, an email, a text message, and standard mail.

11. A selection method, comprising:

providing a database system comprising a first database structure storing a first list identifying marketing events and a third list of value scores, a second database structure storing a second list of candidates, a third database structure storing at least one data model, and a database manager software application stored on a computer readable medium, wherein said database manager software application comprises a grouping tool, a computing tool, and an optimization tool, wherein each marketing event from said first list comprises a marketing offer and an identified channel means for communicating said marketing offer, wherein each value score from said third list is associated with a marketing event from said first list, wherein said value scores are associated with an expected profit gain associated with each said marketing offer, and wherein said marketing events from said first list are divided into a first plurality of groups;

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 a 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 a 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 first list in response to said first determining and said second determining, said first marketing event;

dividing by said grouping tool, candidates from said second list of candidates into a second plurality of groups;

matching by said grouping tool, a first group from said first plurality of groups with a second group from said second plurality of groups, wherein all candidates from said second group comprise a first specified candidate trait;

computing, by said computing tool, response probability scores for said marketing events from said first group for all of said candidates within said second group, 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 from said first group for all of said candidates from said second group, wherein each of said ranking scores are computed by multiplying a value score from said third list with an associated response probability score of said response probability scores;

optimizing, by a computer processor of said database system, said marketing events from said first group for all of said candidates from said second group, said computer processor executing said optimization tool to perform said optimizing; and

sorting, by said optimization tool, said marketing events from said first group for all of said candidates from said second group, wherein said marketing events from said first group are optimized and sorted for all of said candidates from said second group by optimizing and sorting said ranking scores for each of said marketing events from said from said first group.

12. The method of claim 11 further comprising:

matching by said grouping tool, a third group from said first plurality of groups with a fourth group from said second plurality of groups, wherein all candidates from said fourth group comprise a second specified candidate trait, wherein said first specified candidate trait comprises a different candidate trait than said second specified candidate trait;

optimizing, by said optimization tool, said marketing events from said third group for all candidates from said fourth group; and

sorting, by said optimization tool, said marketing events from said third group for all of said candidates from said fourth group.

13. The method of claim 11, further comprising generating by the optimization tool, a priority list comprising said sorted marketing events from said first group, and wherein said priority list prioritizes an order in which to offer each of said marketing events from said first group to all of said candidates from said second group.

14. The method of claim 11, further comprising generating by the optimization tool, a priority list comprising a first set of marketing events from said sorted marketing events from said first group that fall within a specified set of constraints, and wherein said priority list is for prioritizing an order in which to offer each of said marketing events from said first group to all of said candidates from said second group.

15. The method of claim 14, wherein said specified set of constraints comprise timing conflicts related to offering all of said marketing events from said first group.

16. The database system of claim 14, wherein said specified set of constraints comprise budget constraints related to offering all of said marketing events from said first group.

17. The method of claim 11, wherein said list of candidates comprises existing customers of an entity that is offering said plurality of marketing events.

18. The method of claim 11, wherein said marketing events from said first group are sorted and optimized essentially simultaneously.

19. The method of claim 11, wherein each marketing offer is selected from the group consisting of a product offer and a service offer.

20. The method of claim 11, wherein each identified channel means is selected from the group consisting of a telephone call, an email, a text message, and standard mail.

31. The method of claim 11, further comprising:

removing, by said optimization tool from said third list, a third marketing event of said first group; and

reallocating, by said optimization tool, monetary funds associated with said third marketing event to a fourth market event of said first group.

21. 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 method for ordering a first list identifying of marketing events within a database system, said database system comprising a first database structure storing said first list identifying marketing events and a third list of value scores, a second database structure storing a second list of candidates, a third database structure storing at least one data model, and a database manager software application stored on a computer readable medium, wherein said database manager software application comprises a grouping tool, a computing tool, and an optimization tool, wherein each marketing event from said first list comprises a marketing offer and an identified channel means for communicating said marketing offer, wherein each value score from said third list is associated with a marketing event from said first list, wherein said value scores are associated with an expected profit gain associated with each said marketing offer, wherein said marketing events from said first list are divided into a first plurality of groups, said method comprising the steps of:

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 a 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 first list in response to said first determining and said second determining, said first marketing event;

dividing by said grouping tool, candidates from said second list of candidates into a second plurality of groups;

matching by said grouping tool, a first group from said first plurality of groups with a second group from said second plurality of groups, wherein all candidates from said second group comprise a first specified candidate trait;

computing, by said computing tool, response probability scores for said marketing events from said first group for all of said candidates within said second group, 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 from said first group for all of said candidates from said second group, wherein each of said ranking scores are computed by multiplying a value score from said third list with an associated response probability score of said response probability scores;

optimizing, by a computer processor of said database system, said marketing events from said first group for all of said candidates from said second group, said computer processor executing said optimization tool to perform said optimizing; and

sorting, by said optimization tool, said marketing events from said first group for all of said candidates from said second group, wherein said marketing events from said first group are optimized and sorted for all of said candidates from said second group by optimizing and sorting said ranking scores for each of said marketing events from said from said first group.

22. The computer program product of claim 21, wherein said method further comprises:

matching by said grouping tool, a third group from said first plurality of groups with a fourth group from said second plurality of groups, wherein all candidates from said fourth group comprise a second specified candidate trait, wherein said first specified candidate trait comprises a different candidate trait than said second specified candidate trait;

optimizing, by said optimization tool, said marketing events from said third group for all candidates from said fourth group; and

sorting, by said optimization tool, said marketing events from said third group for all of said candidates from said fourth group.

23. The computer program product of claim 21, wherein said method further comprises generating by the optimization tool, a priority list comprising said sorted marketing events from said first group, and wherein said priority list prioritizes an order in which to offer each of said marketing events from said first group to all of said candidates from said second group.

24. The computer program product of claim 21, wherein said method further comprises generating by the optimization tool, a priority list comprising a first set of marketing events from said sorted marketing events from said first group that fall within a specified set of constraints, and wherein said priority list is for prioritizing an order in which to offer each of said marketing events from said first group to all of said candidates from said second group.

25. The computer program product of claim 24 wherein said specified set of constraints comprise timing conflicts related to offering all of said marketing events within said first group.

26. The computer program product of claim 24, wherein said specified set of constraints comprise budget constraints related to offering all of said marketing events within said first group.

27. The computer program product of claim 21, wherein said list of candidates comprises existing customers of an entity that is offering said plurality of marketing events.

28. The computer program product of claim 21, wherein said marketing events from said first group are sorted and optimized essentially simultaneously.

29. The computer program product of claim 21, wherein each marketing offer is selected from the group consisting of a product offer and a service offer.

30. The computer program product of claim 21, wherein each identified channel means is selected from the group consisting of a telephone call, an email, a text message, and standard mail.