Advertisement selection system supporting discretionary target market characteristics

• US 20010004733A1
• Filed: 01/31/2001
• Published: 06/21/2001
• Est. Priority Date: 03/12/1999
• Status: Active Grant

• Current Assignee: Prime Research Alliance E, LLC
• Original Assignee: Expanse Networks, Inc.
• Inventors: Eldering, Charles A.
• Granted Patent: US 6,560,578 B2
• 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 computer implemented method for selecting a targeted advertisement to be presented to a consumer by determining similarities between a profile of the consumer which is generated in part from purchase records of the consumer and a profile for each of a plurality of advertisements, wherein the profile for each advertisement identifies discretionary characteristics of an intended target market of the advertisement, the method comprising:

receiving the consumer profile;

receiving the plurality of advertisement profiles;

comparing each advertisement profile with the consumer profile to determine a correlation value between each advertisement profile and the consumer profile; and

selecting a targeted advertisement to be presented to a particular consumer based on correlation values.

2. The method of

claim 1

, wherein each advertisement profile is identified by a unique identifier.

3. The method of

claim 1

, wherein

each advertisement profile includes a demographic characterization of an intended target market;

the consumer profile includes a demographic characterization of the consumer; and

said comparing includes determining a correlation value between the demographic characterization of the intended target market and the demographic characterization of the consumer.

4. The method of

claim 1

, wherein

each advertisement profile includes a product preference characterization of the intended target market;

the consumer profile includes a product preference characterization of the consumer; and

said comparing includes determining a correlation value between the product preference characterization of the intended target market and the product preference characterization of the consumer.

5. The method of

claim 1

, further comprising determining a price to present the targeted advertisement to the consumer, wherein the price is based on the determined correlation value.

6. The method of

claim 5

, wherein the price is an increasing monotonic function of the correlation value.

7. The method of

claim 6

, wherein the price is a decreasing monotonic function of the correlation value.

8. The method of

claim 1

, wherein the purchase records are accumulated in at least one external database.

9. The method of

claim 1

, wherein the purchase records are accumulated from multiple point-of-sale transactions.

10. The method of

claim 9

, wherein the multiple point-of-sale transactions are transacted at a plurality of locations.

11. The method of

claim 1

, further comprising presenting the targeted advertisement to the consumer via a television.

12. The method of

claim 1

, wherein the consumer profile includes one or more vectors, each vector representing probabilistic information associated with the consumer.

13. The method of

claim 12

, wherein the probabilistic information includes one or more probabilistic demographic characterization vectors, each probabilistic demographic characterization vector based on a representation of a probability that a consumer falls within a certain demographic category.

14. The method of

claim 13

, wherein each demographic characterization vector is further based on one or more interest categories.

15. The method of

claim 12

, wherein the probabilistic information includes one or more product preference categories, wherein each product preference category represents the average of consumer preferences over past purchases.

16. The method of

claim 1

, wherein the consumer profile further includes deterministic information corresponding to the consumer.

17. The method of

claim 1

, wherein the consumer profile is further based on one or more television viewing transactions.

18. The method of

claim 1

, wherein said retrieving the consumer profile comprises:

retrieving a detailed transaction record, wherein the detailed transaction record includes an inventory of multiple transactions which occurred over a predetermined time interval; and

generating the consumer profile from the detailed transaction record.

19. The method of

claim 18

, wherein:

said retrieving the consumer profile further comprises retrieving a set of heuristic rules associated with transactions within the detailed transaction record, the set of heuristic rules defining a probabilistic measure of demographic characteristics of a person performing the transactions; and

said generating comprises generating the consumer profile from the detailed purchase transaction record and the set of heuristic rules.

20. The method of

claim 18

, wherein said retrieving a detailed transaction record includes:

storing the multiple transactions of the consumer; and

generating the detailed transaction record based on the stored transactions.

21. A computer system for selecting a targeted advertisement to be presented to a consumer by determining similarities between a profile of the consumer and a plurality of advertisement profiles, each advertisement profile identifying discretionary characteristics of an intended target market of the advertisement, the system comprising:

a storage medium;

means for receiving a plurality of advertisement profiles;

means for retrieving a consumer profile, wherein the consumer profile is derived in part from corresponding purchase records;

means for calculating a correlation value between each advertisement profile and the consumer profile; and

means for selecting a targeted advertisement to present to the consumer based on the correlation values.

22. The system of

claim 21

, further comprising means for accumulating detailed purchase records from a plurality of point of sale transactions, wherein the consumer profile is derived in part from the detailed purchase records.

23. The system of

claim 21

, further comprising:

means for retrieving a pricing function; and

means for determining a price for displaying the targeted advertisement to the consumer, wherein the price is determined from the correlation value and the pricing function.

24. The system of

claim 21

, further comprising means for transmitting the targeted advertisement to the consumer.

25. The system of

claim 21

, wherein the means for retrieving a consumer profile includes:

means for retrieving a detailed purchase record of the consumer;

means for retrieving a set of heuristic rules associated with products included in the detailed purchase records, wherein the set of heuristic rules define a probabilistic measure of demographic characteristics of a purchaser of corresponding products; and

means for generating the consumer profile from the detailed purchase records and the set of heuristic rules.

26. A computer program embodied on a computer-readable medium for selecting a targeted advertisement for a consumer by comparing a profile of the consumer to a profile of each of a plurality of advertisements, wherein each advertisement profile identifies specific characteristics of an intended target market of the advertisement, the computer program comprising:

a source code segment for receiving a plurality of advertisement profiles;

a source code segment for retrieving the consumer profile, wherein the consumer profile is partly derived from purchase records; and

a source code segment for determining a correlation value between each advertisement profile and the consumer profile; and

a source code segment for selecting a targeted advertisement to present to the consumer based on correlation values.

27. The computer program of

claim 26

, further comprising a source code segment for transmitting the determined correlation values to advertisers.

28. A computer implemented method for presenting selected advertisements to a consumer based on how applicable the selected advertisements are to the consumer, the method comprising:

receiving a consumer profile, wherein the consumer profile identifies discretionary characteristics of the consumer and is generated based on transactions made by the consumer;

receiving a plurality of advertisement profiles, wherein each advertisement profile identifies discretionary characteristics of consumers in an intended target market for an associated advertisement;

determining a correlation value between each advertisement profile and the consumer profile; and

selecting one or more advertisements to be presented to the consumer based on the correlation values; and

presenting the one or more selected advertisements to the consumer.

29. The method of

claim 28

, wherein

the discretionary characteristics identified in the consumer profile include a demographic characterization of the consumer;

the discretionary characteristics identified in each advertisement profile include a demographic characterization of consumers in the intended target market; and

said determining includes determining a correlation value between each demographic characterization of consumers in the intended target market and the demographic characterization of the consumer.

30. The method of

claim 28

, wherein said receiving a consumer profile includes:

receiving a transaction record for each of the transactions made by the consumer;

retrieving a set of heuristic rules associated with each transaction, the set of heuristic rules defining a probabilistic measure of demographic characteristics of a person performing the transaction; and

generating the consumer profile from the transaction records and the set of heuristic rules.

31. The method of

claim 28

, wherein said presenting the one or more selected advertisements to the consumer includes presenting the one or more selected advertisements to the consumer via a television.

32. The method of

claim 28

, wherein the transactions made by the consumer include at least one of the following transactions:

point of sale purchases;

Internet browsing sessions;

Internet purchases; and

television viewing sessions.

33. The method of

claim 28

, wherein said selecting includes selecting the one or more advertisements with highest correlation values.

34. The method of

claim 28

, wherein said selecting includes selecting the one or more advertisements exceeding a predetermined correlation value.