METHOD AND APPARATUS FOR OBTAINING REVENUE FROM THE DISTRIBUTION OF HYPER-RELEVANT ADVERTISING THROUGH PERMISSIVE MIND READING, PROXIMITY ENCOUNTERS, AND DATABASE AGGREGATION

• US 20070112762A1
• Filed: 10/25/2006
• Published: 05/17/2007
• Est. Priority Date: 10/25/2005
• Status: Active Grant

• Current Assignee: V!E, Inc.
• Original Assignee: V!E, Inc.
• Inventors: Brubaker, Curtis
• Granted Patent: US 9,299,077 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method and apparatus enabling the distribution of hyper-relevant advertising to consumers who have confirmed interests in specific content, products, and services is described. Users define “who they are” and “what they want” in a spontaneous, guided, voluntary disclosure of rich, candid, personal information conceived to attract individuals who seek or share common relationships, experiences, objectives, skills, knowledge, acquaintances, interests, needs, or desires for mutual gain. The information is converted into encrypted user codes; these codes are used to generate precisely controlled electronic encounters, the creation and delivery of highly personalized hyper-relevant advertising, and the gathering of amounts of research data through the ad hoc interaction of unique mobile devices.

Claims

1. A computer implemented method, comprising:

compiling a unique profile of a user based on computer analysis of data provided by the user;

rewarding the user for providing the data; and

displaying hyper-relevant information to the user based on said unique profile.

2. A method as recited in claim 1:

wherein said data comprises specific information regarding who the user is.

3. A method as recited in claim 1:

wherein said data comprises specific information regarding what the user wants.

4. A method as recited in claim 3:

wherein said hyper-relevant information is selected based solely on said specific information regarding what the user wants.

5. A method as recited in claim 1:

wherein the rewarding step is performed by an entity that acquires said data.

6. A method as recited in claim 1:

wherein the rewarding step is performed by an entity that is a source of said hyper-relevant information.

7. A method as recited in claim 6:

wherein said source of said hyper-relevant information is a third party.

8. A method as recited in claim 6:

wherein said source of said hyper-relevant information is an advertiser, an ad agency, or a creator of said hyper-relevant information.

9. A method as recited in claim 6:

wherein said source of said hyper-relevant information is a central server.

10. A method as recited in claim 6:

wherein said source of said hyper-relevant information is a collection of passively-acquired data.

11. A method as recited in claim 1:

wherein said hyper-relevant information comprises details related to an opportunity available to the user.

12. A method as recited in claim 11:

wherein said opportunity comprises an opportunity for the user to display hyper-relevant information to others.

13. A method as recited in claim 12:

wherein the user receives revenue for displaying hyper-relevant information to others.

14. A method as recited in claim 11:

wherein said opportunity comprises an opportunity for the user to receive revenue for viewing hyper-relevant information presented by others.

15. A method as recited in claim 1:

wherein said hyper-relevant information comprises details related to a personal encounter.

16. A method as recited in claim 15:

wherein a subset of another user'"'"'s profile is sent to the user for review.

17. A method as recited in claim 15:

wherein the user can escalate, terminate, or store said information related to a personal encounter.

18. A method as recited in claim 15, further comprising:

sending a subset of the user'"'"'s profile to another user;

wherein said subset of the user'"'"'s profile was pre-selected by the user for sending to others.

19. A method as recited in claim 15, further comprising:

successively exchanging profile content with a plurality of other users until an encounter occurs, is postponed, or is terminated;

wherein said profile content is exchanged according to a predetermined script, without inputting additional profile content prior to consummation, termination, or postponement of said encounter.

20. A method as recited in claim 1:

wherein said hyper-relevant information comprises details related to advertising.

21. A method as recited in claim 1, wherein the compiling step comprises:

conversion of said data to a non-identifiable (NID) format; and

uploading said NID-formatted content to a central server;

wherein analysis of said NID-formatted content influences presentation of said hyper-relevant information displayed to the user.

22. A method as recited in claim 1, wherein analysis of data provided by the user comprises:

identifying relational aspects of said data; and

expressing said relational aspects according to a system of user codes;

wherein said hyper-relevant information displayed to the user is determined according to said user codes.

23. A method as recited in claim 1, further comprising:

updating said profile with new data;

wherein said new data comprises responses of the user to said hyper-relevant information.

24. A method as recited in claim 1, further comprising:

updating said profile with new data;

wherein said new data is acquired in a passive manner from a mobile device.

25. A method as recited in claim 1:

wherein the user is a member of a particular community; and

wherein the user receives said hyper-relevant information in exchange for access to other users in communities other than the user'"'"'s particular community.

26. A method as recited in claim 1, wherein said unique profile comprises:

data regarding who the user is;

data regarding what the user wants;

data regarding the user'"'"'s past responses to said hyper-relevant information; and

data regarding the user'"'"'s habitual locations.

27. A method as recited in claim 26, wherein said data regarding the user'"'"'s habitual locations comprises data regarding time of day.

28. A method as recited in claim 26, wherein said unique profile further comprises:

data regarding agreement between what the user wants and the user'"'"'s past responses to displayed hyper-relevant information.

29. A method as recited in claim 26, wherein said unique profile further comprises:

data regarding the user'"'"'s potential future locations.

30. A method as recited in claim 1, wherein said unique profile comprises:

a plurality of access rights to content of said unique profile;

wherein a subset of selected content is accessible to one or more third parties under specific conditions.

31. A method as recited in claim 1;

wherein content of said unique profile is available for purchase by a third party; and

wherein the user cannot be identified by said content available for purchase.

42. A method as recited in claim 2:

wherein said hyper-relevant information is selected based solely on said specific information regarding who the user is.

32. A computer implemented method, comprising:

acquiring data from a first user;

wherein said data is actively provided by the first user;

rewarding the first user for providing said data;

analyzing said data;

compiling a unique profile of the first user based on computer analysis of said data; and

displaying hyper-relevant information to the first user;

wherein said hyper-relevant information is individually selected for the first user based on said profile without human intervention.

33. A method as recited in claim 32, further comprising:

compiling a unique profile for each of a plurality of users; and

populating a central server with unique profiles for each of the users from whom data is acquired.

34. A method as recited in claim 32, further comprising:

compiling a unique profile for each of a plurality of users; and

storing a unique profile for each individual user on a mobile device belonging to that user.

35. A method as recited In claim 34, further comprising:

selecting at least one unique profile of another user based on computer analysis of said data acquired from the first user; and

storing said selected at least one unique profile of another user on a mobile device belonging to said first user.

36. A computer implemented method, comprising:

compiling a unique profile of a user based on computer analysis of data provided by the user;

storing said unique profile of the user on a mobile device;

rewarding the user for providing the data;

displaying hyper-relevant information to the user based on said unique profile;

updating said unique profile with data related to responses by the user to said hyper-relevant information; and

transmitting said updated unique profile to other receiving devices in range;

wherein additional hyper-relevant information is displayed to the user based on said updated unique profile.

37. A computer implemented method, comprising:

compiling a unique profile of a user based on computer analysis of data provided by the user;

rewarding the user for providing the data;

exchanging unique profile data between a plurality of users in a location;

wherein the exchanging step is performed without user input;

comparing unique profile data of each user to each of said plurality of users; and

displaying hyper-relevant information to the user based on the comparison of the unique profile of that user to the unique profile of other users.

38. A system, comprising:

a computer; and

programming executable on said computer for performing the steps of;

compiling a unique profile of a user based on analysis of data provided by the user;

rewarding the user for providing the data; and

displaying hyper-relevant information to the user based on said unique profile.

39. A system, comprising:

a computer; and

programming executable on said computer for performing the steps of;

acquiring data from a user;

wherein said data is actively provided by the user;

rewarding the user for providing said data;

analyzing said data;

compiling a unique profile of the user based on analysis of said data; and

displaying hyper-relevant information to the user;

wherein said hyper-relevant information is individually selected for the user based on said profile without human intervention.

40. A system, comprising:

a computer; and

programming executable on said computer for performing the steps of;

compiling a unique profile of a user based on analysis of data provided by the user;

storing said unique profile of the user on a mobile device;

rewarding the user for providing the data;

displaying hyper-relevant information to the user based on said unique profile;

updating said unique profile with data related to responses by the user to said hyper-relevant information; and

transmitting said updated unique profile to other receiving devices in range;

wherein additional hyper-relevant information is displayed to the user based on said updated unique profile.

41. A system, comprising:

a computer; and

programming executable on said computer for performing the steps of;

compiling a unique profile of a user based on analysis of data provided by the user;

rewarding the user for providing the data;

exchanging unique profile data between a plurality of users in a location;

wherein the exchanging step is performed without user input;

comparing unique profile data of each user to each of said plurality of users; and

displaying hyper-relevant information to the user based on the comparison of the unique profile of that user to the unique profile of other users.