Advertisement selection system supporting discretionary target market characteristics

• US 20030004810A1
• Filed: 08/28/2002
• Published: 01/02/2003
• Est. Priority Date: 03/12/1999
• Status: Abandoned Application

• Current Assignee: Prime Research Alliance E, LLC
• Original Assignee: Prime Research Alliance E, LLC
• Inventors: Eldering, Charles A.
• Application Number:
  US10/229,783
• Publication Number:
  US 20030004810A1
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 20/20 Point-of-sale [POS] network systems
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0237 at kiosk
• CPC Class Codes: G06Q 30/0239 Online discounts or incentives
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0268 at point-of-sale [POS]
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

An advertisement selection system is presented in which vectors describing an actual or hypothetical market for a product or desired viewing audience can be determined. An ad characterization vector is transmitted along with a consumer ID. The consumer ID is used to retrieve a consumer characterization vector which is correlated with the ad characterization vector to determine the suitability of the advertisement to the consumer. The consumer characterization vector describes statistical information regarding the demographics and product purchase preferences of a consumer, and is developed from previous purchases or viewing habits. A price for displaying the advertisement can be determined based on the results of the correlation of the ad characterization vector with the consumer characterization vector.

Claims

1. A method for selecting a targeted advertisement to be presented to a consumer, the method comprising:

receiving a consumer profile that includes discretionary traits about the consumer, wherein the discretionary traits were generated based on transactions made by the consumer but are not directly associated with the transactions;

receiving an advertisement profile for an advertisement, wherein the advertisement profile includes at least discretionary traits of an intended target market of the advertisement;

comparing the advertisement profile with the consumer profile to determine similarities between the advertisement and the consumer; and

selecting the advertisement to be presented to the consumer if said comparing determines they are similar enough.

2. The method of claim 1, wherein the discretionary traits associated with the consumer were generated by applying heuristic rules associated with the transactions made by the consumer to the transactions.

3. The method of claim 1, wherein the discretionary traits include demographic traits.

4. The method of claim 1, wherein the discretionary traits are probabilistic.

5. The method of claim 1, wherein the discretionary traits include product preference traits.

6. The method of claim 1, wherein the discretionary traits include consumer interests.

7. The method of claim 1, wherein

the discretionary traits included in the consumer profile are generated based on transactions in a first field;

and

the advertisement associated with the advertisement profile is for a second field.

8. The method of claim 7, wherein the first field and the second field differ based on at least some subset of product, service, or industry.

9. The method of claim 1, wherein the discretionary traits are used to target advertisements to the consumer that typically would not be directly linked with the transactions.

10. The method of claim 1, wherein said receiving a consumer profile includes receiving consumer transactions;

retrieving heuristic rules associated with at least some subset of the consumer transactions, wherein the heuristic rules predict discretionary traits about the consumer making the transaction;

applying the heuristic rules to the consumer transactions to generate the discretionary traits; and

including the discretionary traits in the consumer profile.

11. The method of claim 10, wherein the heuristic rules assign probabilities for the consumer making the transaction having particular traits.

12. The method of claim 10, wherein the heuristic rules are associated with particular transactions.

13. The method of claim 10, wherein the heuristic rules are associated with an aggregation of transactions.

14. The method of claim 1, wherein the consumer profile further includes deterministic information about the consumer.

15. The method of claim 1, wherein the consumer profile further includes transaction related traits.

16. The method of claim 1, wherein the transactions include consumer purchases.

17. The method of claim 1, wherein the transactions include consumer television interactions.

18. The method of claim 1, wherein the transactions include consumer Internet usage.

19. The method of claim 15, wherein the transaction related traits include purchasing habits.

20. The method of claim 15, wherein the transaction related traits include television viewing habits.

21. The method of claim 15, wherein the transaction related traits include Internet usage habits.

22. The method of claim 1, wherein

said receiving an advertisement profile includes receiving a plurality of advertisement profiles, each of the advertisement profiles including discretionary traits of an intended target market of an associated advertisement;

and

said comparing includes comparing the consumer profile with each of the plurality of advertisement profiles.

23. The method of claim 22, wherein said selecting includes selecting the advertisement that is most similar to the consumer.

24. The method of claim 23, wherein said selecting the advertisement that is most similar to the consumer includes selecting the advertisement that meets a threshold and is the most similar to the consumer.

25. The method of claim 22, wherein said selecting includes selecting all of the plurality of advertisements that meet a threshold.

26. The method of claim 1, further comprising presenting the targeted advertisement to the consumer.

27. The method of claim 26, wherein said presenting includes presenting the advertisement to the consumer via a television.

28. The method of claim 26, wherein said presenting includes presenting the advertisement to the consumer via Internet.

29. The method of claim 26, wherein said presenting includes presenting the advertisement to the consumer via mail.

30. The method of claim 26, wherein said presenting includes presenting the advertisement to the consumer via a point-of-sale checkout.

31. The method of claim 26, wherein said presenting includes presenting the advertisement to the consumer via a kiosk.

32. The method of claim 1, wherein the targeted advertisement is a television commercial.

33. The method of claim 1, wherein the targeted advertisement is an Internet advertisement.

34. The method of claim 1, wherein the targeted advertisement is an in store advertisement.

35. The method of claim 1, wherein the targeted advertisement is a coupon.

37. The system of claim 36, wherein said means for receiving a consumer profile includes

means for receiving consumer transactions;

means for retrieving heuristic rules associated with at least some subset of the consumer transactions, wherein the heuristic rules predict traits about the consumer making the transaction; and

means for generating the discretionary traits included in the consumer profile by applying the heuristic rules to the consumer transactions.

38. The system of claim 36, wherein said means for receiving an advertisement profile receives a plurality of advertisement profiles, each of the advertisement profiles including discretionary traits of an intended target market of an associated advertisement;

and

said means for comparing compares the consumer profile with each of the plurality of advertisement profiles.

39. The system of claim 38, wherein said means for selecting selects the advertisement that is most similar to the consumer.

40. The system of claim 38, wherein said means for selecting selects the advertisement that meets a threshold and is the most similar to the consumer.

41. The system of claim 38, wherein said means for selecting selects all of the plurality of advertisements that meet a threshold.

42. The system of claim 36, further comprising means for presenting the targeted advertisement to the consumer.

43. The system of claim 42, wherein said means for presenting includes a television.

44. The system of claim 42, wherein said means for presenting includes Internet.

45. The system of claim 42, wherein said means for presenting includes mail.

46. The system of claim 42, wherein said means for presenting includes a point-of-sale checkout.

47. The system of claim 42, wherein said means for presenting includes a kiosk.

49. The computer program of claim 48, wherein said source code segment for receiving a consumer profile includes

a source code segment for receiving consumer transactions;

a source code segment for retrieving heuristic rules associated with at least some subset of the consumer transactions, wherein the heuristic rules predict traits about the consumer making the transaction; and

a source code segment for generating the discretionary traits included in the consumer profile by applying the heuristic rules to the consumer transactions.

50. The computer program of claim 48, wherein said source code segment for receiving an advertisement profile receives a plurality of advertisement profiles, each of the advertisement profiles including discretionary traits of an intended target market of an associated advertisement;

and

said source code segment for comparing compares the consumer profile with each of the plurality of advertisement profiles.

51. The computer program of claim 50, wherein said source code segment for selecting selects the advertisement that is most similar to the consumer.

52. The computer program of claim 50, wherein said source code segment for selecting selects the advertisement that meets a threshold and is the most similar to the consumer.

53. The computer program of claim 54, wherein said source code segment for selecting selects all of the plurality of advertisements that meet a threshold.

54. The computer program of claim 48, further comprising a source code segment for presenting the targeted advertisement to the consumer.

36. A system for selecting a targeted advertisement to be presented to a consumer, the system comprising:

means for receiving a consumer profile that includes discretionary traits about the consumer, wherein the discretionary traits were generated based on transactions made by the consumer but are not directly associated with the transactions;

means for receiving an advertisement profile for an advertisement, wherein the advertisement profile includes at least discretionary traits of an intended target market of the advertisement;

means for comparing the advertisement profile with the consumer profile to determine similarities between the advertisement and the consumer; and

means for selecting the advertisement to be presented to the consumer if said comparing determines they are similar enough.

48. A computer program embodied on a computer readable medium for selecting a targeted advertisement to be presented to a consumer, the computer program comprising:

a source code segment for receiving a consumer profile that includes discretionary traits about the consumer, wherein the discretionary traits were generated based on transactions made by the consumer but are not directly associated with the transactions;

a source code segment for receiving an advertisement profile for an advertisement, wherein the advertisement profile includes at least discretionary traits of an intended target market of the advertisement;

a source code segment for comparing the advertisement profile with the consumer profile to determine similarities between the advertisement and the consumer; and

a source code segment for selecting the advertisement to be presented to the consumer if said comparing determines they are similar enough.

55. A method for identifying consumers to be targeted with an advertisement, the method comprising:

retrieving a plurality of consumer profiles, wherein each consumer profile is based at least in part on recorded transactions associated with the consumer and identifies at least one discretionary trait of the consumer that is not directly associated with the recorded transactions;

retrieving an advertisement profile associated with the advertisement, wherein the advertisement profile identifies at least one discretionary trait of an intended market for the advertisement; and

identifying a set of consumers to receive the advertisement by correlating the advertisement profile with at least a subset of the consumer profiles.

56. The method of claim 55, wherein the discretionary traits associated with the consumer were generated by applying heuristic rules associated with the transactions made by the consumer to the transactions.

57. The method of claim 55, wherein the discretionary traits associated with the consumer are used to target advertisements to the consumer that typically would not be directly linked with the transactions.

58. The method of claim 55, wherein said retrieving a plurality of consumer profiles includes

receiving consumer transactions for a plurality of consumers;

retrieving heuristic rules associated with at least some subset of the consumer transactions, wherein the heuristic rules predict discretionary traits about the consumer making the transaction; and

applying the heuristic rules to the consumer transactions to generate the discretionary traits.

59. The method of claim 56, wherein the heuristic rules are associated with particular transactions.

60. The method of claim 56, wherein the heuristic rules are associated with an aggregation of transactions.

61. The method of claim 55, wherein the discretionary traits include demographic traits.

62. The method of claim 55, wherein the discretionary traits are probabilistic.

63. The method of claim 55, wherein the discretionary traits include at least some subset of product preference traits and consumer interests.

64. The method of claim 55, further comprising presenting the advertisement to the set of consumers.

65. A system for identifying consumers to be targeted with an advertisement, the system comprising:

means for retrieving a plurality of consumer profiles, wherein each consumer profile is based at least in part on recorded transactions associated with the consumer and identifies at least one probabilistic discretionary trait of the consumer that is not directly associated with the recorded transactions;

means for retrieving an advertisement profile associated with the advertisement, wherein the advertisement profile identifies at least one discretionary trait of an intended market for the advertisement; and

means for identifying a set of consumers to receive the advertisement by correlating the advertisement profile with at least a subset of the consumer profiles.

66. The system of claim 65, wherein said means for retrieving a plurality of consumer profiles includes

means for receiving consumer transactions for a plurality of consumers;

means for retrieving heuristic rules associated with at least some subset of the consumer transactions, wherein the heuristic rules predict discretionary traits about the consumer making the transaction; and

means for applying the heuristic rules to the consumer transactions to generate the discretionary traits.

68. The computer program of claim 67, wherein said source code segment for retrieving a plurality of consumer profiles includes

a source code segment for receiving consumer transactions for a plurality of consumers;

a source code segment for retrieving heuristic rules associated with at least some subset of the consumer transactions, wherein the heuristic rules predict discretionary traits about the consumer making the transaction; and

a source code segment for applying the heuristic rules to the consumer transactions to generate the discretionary traits.

67. A computer program embodied on a computer readable medium for identifying consumers to be targeted with an advertisement, the computer program comprising:

a source code segment for retrieving a plurality of consumer profiles, wherein each consumer profile is based at least in part on recorded transactions associated with the consumer and identifies at least one probabilistic discretionary trait of the consumer that is not directly associated with the recorded transactions;

a source code segment for retrieving an advertisement profile associated with the advertisement, wherein the advertisement profile identifies at least one discretionary trait of an intended market for the advertisement; and

a source code segment for identifying a set of consumers to receive the advertisement by correlating the advertisement profile with at least a subset of the consumer profiles.