Electronic coupons decision support and recommendation system

• US 8,452,652 B2
• Filed: 01/29/2001
• Issued: 05/28/2013
• Est. Priority Date: 01/29/2001
• Status: Active Grant

• Current Assignee: Rakuten Group, Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Barik, Rajkishore, Mittal, Parul A
• Primary Examiner(s): Bekerman, Michael
• Application Number:
  US09/772,244
• Publication Number:
  US 20020143612A1
• Time in Patent Office: 4,502 Days
• Field of Search: 705/14.23, 705/14.39, 705/14.51
• US Class Current: 705/14.23
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0222 During e-commerce, i.e. online transactions
• CPC Class Codes: G06Q 30/0224 based on user history
• CPC Class Codes: G06Q 30/0225 Avoiding frauds

Abstract

A method, an apparatus, and a computer program product for determining a combination of electronic coupons (e-coupons) for redemption by a retailer in a networked environment are disclosed. In the method, a check is made to determine if a selection of e-coupons complies with redeeming conditions for a purchase. If so, a further check is made to determine if two or more of the selected e-coupons are mutually exclusive. The selection of e-coupons complying with the redeeming conditions and being non-mutually exclusive is displayed. Preferably, the method includes suggesting to a user of an optimal or near optimal selection of e-coupons. The e-coupons may reside at a user'"'"'s site, a third party'"'"'s site, or a site of the retailer in the networked environment. The networked environment may be the Internet, an Intranet, an Extranet, a local area network, an ATM network, a wide area network and a wireless network.

Claims

1. A computer-implemented method of making an optimized suggestion to a user regarding a combination of electronic coupons (e-coupons) for redemption by a retailer, said method comprising:

determining, by said computer, if a selection of e-coupons complies with redeeming conditions in relation to a purchase;

checking said selection of e-coupons complying with said redeeming conditions, by said computer, to determine mutually exclusive e-coupons of said selection of e-coupons applicable within said purchase, and to determine if two or more non-mutually exclusive e-coupons of said selection of e-coupons can be used in combination within said purchase;

defining optimization parameters by a user;

performing an optimization process, by said computer, on said selection of e-coupons to maximize a discount amount, a number of loyalty points, and a number of free items, by checking said selection of e-coupons complying with said redeeming conditions and capable of being used in combination within said purchase to determine if said selection of e-coupons satisfy said optimization parameters, said optimization process determining a most favorable combination of non-mutually exclusive e-coupons;

before said user makes said purchase, outputting a suggestion to said user, by said computer, displaying said most favorable combination of non-mutually exclusive e-coupons based on said determining said mutually exclusive e-coupons, said most favorable combination of non-mutually exclusive e-coupons comprising only said selection of e-coupons complying with said redeeming conditions and capable of being used in combination within said purchase;

saving said displayed most favorable combination of non-mutually exclusive e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase and choosing another subset of said e-coupons;

choosing one of saved sets of e-coupons based on comparing two or more of said saved sets of e-coupons; and

recommending to said user to use an additional e-coupon in relation to said purchase based on said choosing one of said saved sets of e-coupons.

2. The method according to claim 1, further including the step of selecting by a user said selection of e-coupons from a plurality of e-coupons.

3. The method according to claim 1, further including the step of providing a recommendation to a user regarding an additional purchase enabling said user to avail of more discounts.

4. The method according to claim 1, wherein said checking of said selection of e-coupons comprises checking e-coupons that reside at any one of the group consisting of a user'"'"'s site, a third party'"'"'s site, and a site of said retailer in said networked environment.

5. The method according to claim 1, wherein said networked environment is implemented utilizing one or more of the group consisting of the Internet, and Intranet, and Extranet, a local area network, an ATM network, a wide area network and a wireless network.

6. The method according to claim 1, wherein said optimization process is limited by parameters comprising which e-coupons should be included, an expiration date of said e-coupons, and a total number of e-coupons used.

7. A computer program product having a computer readable medium having a computer program recorded therein for making an optimized suggestion to a user regarding a combination of electronic coupons (e-coupons) for redemption by a retailer, said computer program product performing a method comprising:

determining if a selection of e-coupons complies with redeeming conditions in relation to a purchase;

checking said selection of e-coupons complying with said redeeming conditions to determine mutually exclusive e-coupons of said selection of e-coupons applicable within said purchase, and to determine if two or more non-mutually exclusive e-coupons of said selection of e-coupons can be used in combination within said purchase;

defining optimization parameters by a user;

performing an optimization process on said selection of e-coupons to maximize a discount amount, a number of loyalty points, and a number of free items, by checking said selection of e-coupons complying with said redeeming conditions and capable of being used in combination within said purchase to determine if said selection of e-coupons satisfy said optimization parameters, said optimization process determining a most favorable combination of non-mutually exclusive e-coupons;

before said user makes said purchase, outputting a suggestion to said user displaying said most favorable combination of non-mutually exclusive e-coupons based on said determining said mutually exclusive e-coupons, said most favorable combination of non-mutually exclusive e-coupons comprising only said selection of e-coupons complying with said redeeming conditions and capable of being used in combination within said purchase;

saving said displayed most favorable combination of non-mutually exclusive e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase and choosing another subset of said e-coupons;

choosing one of saved sets of e-coupons based on comparing two or more of said saved sets of e-coupons; and

recommending to said user to use an additional e-coupon in relation to said purchase based on said choosing one of said saved sets of e-coupons.

8. The computer program product according to claim 7, further including selecting by a user said selection of e-coupons from a plurality of e-coupons.

9. The computer program product according to claim 7, further including providing a recommendation to a user regarding an additional purchase enabling said user to avail of more discounts.

10. The computer program product according to claim 7, wherein said checking of said selection of e-coupons comprises checking e-coupons that reside at any one of the group consisting of a user'"'"'s site, a third party'"'"'s site, and a site of said retailer in said networked environment.

11. The computer program product according to claim 7 wherein said optimization process is limited by parameters comprising which e-coupons should be included, an expiration date of said e-coupons, and a total number of e-coupons used.

12. A computer-implemented method for electronic coupon (e-coupon) decision support, said method comprising:

computing, by said computer, a set of applicable e-coupons dependent upon a set of e-coupons of a user;

determining, by said computer, if said computed set of e-coupons complies with one or more redeeming conditions, which of said set of e-coupons are mutually exclusive within a same purchase and which of said set of e-coupons are non-mutually exclusive to be used in combination within the same purchase;

performing an optimization process, by said computer, on said selection of e-coupons to maximize a discount amount, a number of loyalty points, and a number of free items, by determining if said computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase satisfy optimization parameters defined by said user, wherein said optimization parameters comprise at least one of a discount amount, loyalty points, a number of free items received, whether at least one particular e-coupon should be included, whether at least one particular e-coupon should not be included, expiration date, and a total number of e-coupons used, said optimization process determining a most favorable combination of non-mutually exclusive e-coupons;

before said user makes said purchase, outputting a suggestion to said user, by said computer, displaying said most favorable combination of non-mutually exclusive e-coupons based on said determining said mutually exclusive e-coupons, said most favorable combination of non-mutually exclusive e-coupons comprising only said computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase that satisfy said optimization parameters;

saving said displayed, computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase and choosing another subset of said e-coupons;

comparing by a user two or more saved sets of e-coupons and choosing one of saved sets of e-coupons; and

recommending to said user to use an additional e-coupon in relation to said purchase based on said choosing one of said saved sets of e-coupons.

13. The method according to claim 12, wherein said computing step is also dependent upon order information.

14. The method according to claim 12, further including the steps of, if said computed set of e-coupons contains at least one e-coupon failing to comply with said redeeming conditions:

displaying said computed set of e-coupons; and

enabling said user to select another set of e-coupons for use in said computing step.

15. The method according to claim 14, further including the step of:

displaying exclusive e-coupons in said another selected set of e-coupons to said user.

16. The method according to claim 15, further including the step of:

displaying e-coupons in said another selected set of e-coupon that are exclusive and fail to comply with said redeeming conditions to said user.

17. The method according to claim 12, further including the step of processing a purchase order for said displayed, computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase.

18. The method according to claim 12, further including the step of recommending to said user a set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase.

19. The method according to claim 12, further including the step of a user viewing reports of e-coupon usage statistics and savings.

20. The method according to claim 12, wherein said finding step is implemented using an optimization engine, said optimization engine addressing one or more conditions selected from the group consisting of:

an AND condition among product purchase redemption conditions;

an AND condition among category purchase redemption conditions;

an XOR condition among product purchase redemption conditions;

an XOR condition among category purchase redemption conditions; and

an e-coupon purchase condition on total amount and e-coupons with heterogeneous purchase conditions.

21. The method according to claim 12, further including the step of:

providing recommendations to said user, based on a profile of said user, in relation to a user selected set of e-coupons.

22. The method according to claim 12, wherein said computing of said set of applicable e-coupons comprises computing e-coupons that reside at any one of the group consisting of a user'"'"'s site, a third party'"'"'s site, and a site of said retailer in said networked environment.

23. A computer program product having a non-transitory computer readable medium having a computer program recorded therein for electronic coupon (e-coupon) decision support, said computer program product including:

computing a set of applicable e-coupons dependent upon a set of e-coupons of a user;

determining if said computed set of e-coupons complies with one or more redeeming conditions, which of said set of e-coupons are mutually exclusive within a same purchase and which of said set of e-coupons are non-mutually exclusive to be used in combination within the same purchase;

performing an optimization process on said selection of e-coupons to maximize a discount amount, a number of loyalty points, and a number of free items, by determining if said computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase satisfy optimization parameters defined by said user, wherein said optimization parameters comprise at least one of a discount amount, loyalty points, a number of free items received, whether at least one particular e-coupon should be included, whether at least one particular e-coupon should not be included, expiration date, and a total number of e-coupons used, said optimization process determining a most favorable combination of non-mutually exclusive e-coupons;

before said user makes a purchase, outputting a suggestion to said user displaying said most favorable combination of non-mutually exclusive e-coupons based on said determining said mutually exclusive e-coupons, said most favorable combination of non-mutually exclusive e-coupons comprising only said computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase that satisfy said optimization parameters;

saving said displayed, computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase and choosing another subset of said e-coupons;

comparing by a user two or more saved sets of e-coupons;

choosing one of said saved sets of e-coupons; and

recommending to said user to use an additional e-coupon in relation to said purchase based on said choosing one of said saved sets of e-coupons.

24. The computer program product according to claim 23, wherein said computing is also dependent upon order information.

25. The computer program product according to claim 23, further including, if said computed set of e-coupons contains at least one e-coupon failing to comply with said redeeming conditions:

displaying said computed set of e-coupons; and

enabling said user to select another set of e-coupons for use in said computing step.

26. The computer program product according to claim 25, further including displaying exclusive e-coupons in said another selected set of e-coupons to said user.

27. The computer program product according to claim 26, further including displaying e-coupons in said another selected set of e-coupons that are exclusive and fail to comply with said redeeming conditions to said user.

28. The computer program product according to claim 23, further including processing a purchase order for said displayed, computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase.

29. The computer program product according to claim 23, further including recommending to said user a set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase.

30. The computer program product according to claim 23, wherein said finding is implemented using an optimization engine, said optimization engine addressing one or more conditions selected from the group consisting of:

an AND condition among product purchase redemption conditions;

an AND condition among category purchase redemption conditions;

an XOR condition among product purchase redemption conditions;

an XOR condition among category purchase redemption conditions; and

an e-coupon purchase condition on total amount and e-coupons with heterogeneous purchase conditions.

31. The computer program product according to claim 23, further including:

providing recommendations to said user, based on said user'"'"'s profile, in relation to a user selected set of e-coupons.

32. The computer program product according to claim 23, wherein said computing of said set of applicable e-coupons comprises computing e-coupons that reside at any one of the group consisting of a user'"'"'s site, a third party'"'"'s site, and a site of said retailer in said networked environment.

33. An electronic coupon (e-coupon) decision support system for making an optimized suggestion to a user regarding a combination of electronic coupons (e-coupons) for redemption by a retailer, said system including:

a hardware module adapted to;

compute a set of applicable e-coupons dependent upon a set of e-coupons of a user;

determine if said computed set of e-coupons complies with one or more redeeming conditions, which of said set of e-coupons are mutually exclusive within a same purchase and which of said set of e-coupons are non-mutually exclusive to be used in combination within the same purchase; and

display only said computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase;

an optimization engine adapted to perform an optimization process on said selection of e-coupons to maximize a discount amount, a number of loyalty points, and a number of free items, by determining a subset of e-coupons from said computed set of e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase, to determine a most favorable combination of non-mutually exclusive e-coupons; and

a user interface adapted to output a suggestion to said user displaying said most favorable combination of non-mutually exclusive e-coupons based on said determining said mutually exclusive e-coupons, said most favorable combination of non-mutually exclusive e-coupons before said user makes said purchase; and

a storage device adapted to save said displayed most favorable combination of non-mutually exclusive e-coupons determined to comply with said redeeming conditions and capable of being used in combination within the same purchase and choosing another subset of said e-coupons, wherein one of saved sets of e-coupons is chosen based on comparing two or more of said saved sets of e-coupons,

wherein said user interface communicates a recommendation to said user to use an additional e-coupon in relation to said purchase based on said choosing one of said saved sets of e-coupons.

34. The system according to claim 33, further including:

a recommendation engine for providing recommendations regarding one or more further purchases to a user, based on said user'"'"'s profile, after said user has selected a set of e-coupons to use.

35. The system according to claim 33, wherein said hardware module, said software module, and said optimization engine are adapted to analyze e-coupons that are located at a retailer'"'"'s site, a user'"'"'s site, or a third party site in a network.

36. The system according to claim 33, wherein said optimization engine is limited by parameters comprising which e-coupons should be included, an expiration date of said e-coupons, and a total number of e-coupons used.