SYSTEM AND METHODOLOGY FOR RECOMMENDING PURCHASES FOR A SHOPPING INTENT

• US 20100088148A1
• Filed: 10/02/2008
• Published: 04/08/2010
• Est. Priority Date: 10/02/2008
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Oath Inc. (Verizon Communications Inc.)
• Inventors: HIGGINS, CHRIS W., PRESSWALA, IRFAN, OTT, EDWARD STANLEY IV, ATHSANI, ATHELLINA, DAVIS, MARC, KALABOUKIS, CHRIS, PARETTI, CHRISTOPHER T.
• Application Number:
  US12/244,121
• Publication Number:
  US 20100088148A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates

Abstract

Techniques are disclosed for optimizing shopping. In one aspect, purchase items are recommended to a user based on the total purchasing costs of the recommended purchase items. In one embodiment, the total purchase cost includes not just the price of the purchase item but also includes weighted costs based on non-price purchasing cost factors. In another aspect, data is maintained that represents social relationships between members of a network of users and purchase recommendations are made to a user based on the relatedness between the user, the item and the other members of the network. In yet another aspect, purchase recommendations are made based on the best time to purchase a purchase item. In another aspect, item retailers can offer purchase item incentives to users based on the identity of and information about the shopper to whom the incentive is offered including bundling incentives in a unified redemption code.

Claims

1. A machine implemented method for recommending purchases, the method comprising:

determining a shopping intent of a user;

determining a candidate set of purchase items that satisfy said shopping intent;

generating a total purchasing cost for each purchase item in the candidate set, wherein the total purchasing cost of each purchase item is based on a set of one or more non-price purchasing cost factors;

wherein the set of one or more non-price purchasing cost factors do not affect how much the user has to pay at the point of sale for the purchase items;

based on the total purchasing costs generated for the purchase items in the candidate set, selecting one or more purchase items, from the candidate set of purchase items, to recommend to the user; and

generating a message that recommends to the user to purchase the selected one or more purchase items;

wherein the method is performed by one or more computing devices.

2. The method of claim 1 further comprising:

determining an indication of weights assigned to one or more non-price purchasing cost factors of the set of non-price purchasing cost factors; and

wherein the step of generating a total purchasing cost for each purchase item in the candidate set is based on the assigned weights.

3. The method of claim 2 wherein the one or more non-price purchasing cost factors that are assigned weights by the user are selected from the group consisting of purchase item quality, purchase item time period, purchase item environmental impact, purchase item sourcing, purchase item relatedness, and purchase item location.

4. The method of claim 2 wherein at least one of the weights is assigned by a user through graphical user interface controls that are caused to be presented to the user at a client.

5. The method of claim 1 wherein determining a shopping intent of a user comprises:

determining at least a portion of the shopping intent based on data that represents purchase items previously related to the user.

6. The method of claim 1 wherein determining a shopping intent of a user comprises:

receiving at least a portion of the shopping intent in a request from the user.

7. The method of claim 6 further comprising:

deriving at least a portion of the shopping intent from a contextual analysis of spatial, temporal, social, and topical data associated with the request from the user.

8. The method of claim 6 wherein the request comprises data that indicates the user'"'"'s physical location and wherein determining a candidate set of purchase items that satisfy the shopping intent comprises determining a candidate set of purchase items that are close in physical proximity to the user'"'"'s physical location.

9. The method of claim 1 wherein the generated message that recommends to the user to purchase the selected one or more purchase items includes the total purchasing cost generated for each selected purchase item.

10. The method of claim 1 wherein one of the non-price purchasing cost factors in the set of non-price purchasing cost factors is purchase item location and wherein generating a message that recommends to the user to purchase the selected one or more purchase items comprises generating a message that includes, for at least one of the selected purchase items, a map that indicates how to travel to a location where the at least one selected purchase item is sold.

11. The method of claim 10 wherein the message indicates, as a monetized value, the cost of traveling to the location where the at least one selected purchase item is sold.

12. The method of claim 10 wherein the message includes a second map that indicates how to travel to an alternative location where the at least one selected purchase item is sold.

13. The method of claim 1 wherein the selected one or more purchase items recommended to the user includes a bundle of one or more of the selected purchase items, and wherein the bundle is associated with a unified redemption code.

14. The method of claim 1 wherein one or more of the selected one or more purchase items to recommend to the user are associated with a purchase item bundle, and wherein the purchase item bundle is associated with a unified redemption code.

15. The method of claim 14 wherein the purchase item bundle is associated with one or more incentives from one or more retailers of the purchase items associated with the purchase item bundle, and wherein the unified redemption code associated with the purchase item bundle refers to the one or more incentives.

23. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 1.

24. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 2.

25. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 3.

26. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 4.

27. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 5.

28. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 6.

29. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 7.

30. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 8.

31. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 9.

32. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 10.

33. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 11.

34. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 12.

35. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 13.

36. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 14.

37. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 15.

45. The method of claim 1, further comprising:

maintaining data that represents degrees of social relationships between members of a network, the user being a member of the network; and

wherein selecting one or more purchase items, from the candidate set of purchase items, to recommend to the user is based on data that represents degrees of social relationships between the user and one or more other users that are also members of the network.

46. The method of claim 1, further comprising:

determining a first cost value that represents the cost of purchasing a purchase item from a particular source during a first time period;

determining second cost value that represents the cost of purchasing a purchase item from said particular source during a second time period;

determining a recommended time period based, at least in part, on said first cost value and said second cost value; and

wherein the message recommends that said user purchase the purchase item from said particular source during the recommended time period.

47. The method of claim 1, further comprising:

storing information that reflects the user'"'"'s selection of one or more of the selected one or more purchase items recommended to the user;

sending a notification message to an item retailer, wherein the notification message alerts the item retailer of the user'"'"'s selection; and

receiving, from the item retailer, information that represents (a) an offer of an incentive to the user of at least one of the one or more purchase items selected by the user and (b) one or more conditions related to the offer of the incentive.

48. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 45.

49. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 46.

50. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 47.

16. A method for recommending purchases, the method comprising:

maintaining data that represents social relationships between members of a network;

determining a shopping intent of a user, the user being a member of the network;

generating a list of recommended purchase items based on the shopping intent of the user and data that represents social relationships between the user and one or more other users that are also members of the network; and

generating a message that recommends to the user to purchase the recommended purchase items in the list of recommended purchase items;

wherein the method is performed by one or more computing devices.

17. The method of claim 16, wherein the data that represents social relationships between the user and at least one of the one or more other users indicates that the user and the at least one other user have a primary relationship with each other.

18. The method of claim 16, wherein generating a list of recommended purchase items is further based on the total purchasing cost of the recommended purchase items, wherein the total purchasing cost is based on one or more non-price purchasing cost factors.

38. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 16.

39. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 17.

40. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 18.

19. A method for recommending purchases, the method comprising:

determining a shopping intent of a user;

identifying a purchase item that satisfies the shopping intent;

determining a first cost value that represents the cost of purchasing the purchase item from a particular source during a first time period;

determining second first cost value that represents the cost of purchasing the purchase item from said particular source during a second time period;

determining a recommended time period based, at least in part, on said first cost value and said second cost value; and

sending a message to the user, wherein the message recommends that said user purchase the purchase item from said particular source during the recommended time period;

wherein the method is performed by one or more computing devices.

20. The method of claim 19 wherein the recommended time period is in the future relative to the time in which the message is sent to the user.

41. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 19.

42. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 20.

21. A method for recommending purchases, the method comprising:

storing information that reflects the user'"'"'s selection of one or more purchase items recommended to the user;

sending a message to an item retailer, wherein the message alerts the item retailer of the user'"'"'s selection; and

receiving, from the item retailer, information that represents (a) an offer of an incentive to the user of at least one of the one or more purchase items selected by the user and (b) one or more conditions related to the offer of the incentive;

wherein the method is performed by one or more computing devices.

22. The method of claim 21, further comprising:

sending a message to the user, wherein the message indicates (a) the offer of the incentive to the user of at least one of the one or more purchase items selected by the user and (b) the one or more conditions related to the offer of the incentive;

receiving, from the user, information that indicates that the user accepts the offer of the incentive and the one or more conditions related to the offer; and

in response to receiving information that indicates that the user accepts the offer and the one or more conditions, modifying the information that reflects the user'"'"'s selection of one or more purchase items recommended to the user.

43. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 21.

44. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 22.