Computer method and apparatus for targeting advertising

• US 20060282328A1
• Filed: 06/12/2006
• Published: 12/14/2006
• Est. Priority Date: 06/13/2005
• Status: Active Grant

• Current Assignee: Rakuten Group, Inc.
• Original Assignee: Gather, Inc.
• Inventors: Gerace, Thomas A., Barbour, Russell G.
• Granted Patent: US 10,510,043 B2
• Time in Patent Office: Days
• US Class Current: 705/14.660
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising

Abstract

In a global network of computers, a method ad system of profiling a user for targeting advertisements is disclosed. The method and system obtains and/or infers demographic information from end-users using on-line means. The invention next monitors end user activity and determines keywords therefrom. The system and method profiles an end user as a function of the determined end-user activity keywords and obtained/inferred end-user demographic information. Profiles of end-users are matched against targeted profiles of advertisements which are defined by the respective advertisers. This results in targeting advertisements to end-users based on end user profiles. Advertisers bid for advertisement placement with the system. In some embodiments, the system employs Vickrey auction type bidding. Using observed user behavior and the auction results, ads are prioritized for selection and viewing placement in a manner that provides the greatest potential value to the system.

Claims

1. In a global network of computers, a method of profiling a user for targeting advertisements, comprising the computer implemented steps of:

obtaining demographic information from end-users using on-line means;

monitoring end user activity and determining keywords therefrom; and

profiling an end user as a function of determined end-user activity keywords and obtained end-user demographic information so as to enable a matching of profiles of end-users to advertisements and thus targeting advertisements to end-users based on end user profiles.

2. A method as claimed in claim 1 wherein the step of obtaining demographic information includes providing an on-line form completed by end-users.

3. A method as claimed in claim 1 wherein the step of obtaining demographic information includes inferring demographics of an end-user.

4. A method as claimed in claim 3 wherein inferring demographics includes:

assuming a Zip Code for the end-user based on Zip Codes detected in end-user activity,

assuming age of the end-user based on ages of others detected in end-user activity,

assuming gender of end-user based on gender of others detected in end-user activity.

5. A method as claimed in claim 1 wherein the step of obtaining demographic information includes soliciting from one end-user demographic data of another end-user.

6. A method as claimed in claim 1 wherein the step of determining keywords includes any combination of:

determining keywords read by an end-user,

determining keywords written by an end-user,

determining keywords searched on by an end-user,

determining keywords browsed by an end-user,

determining keywords forwarded by an end-user,

determining keywords bookmarked by an end-user,

determining keywords in comments of an end-user,

determining keywords received or sent in email messages of the end-user,

recency of a keyword being read or written by an end user, and

frequency of a keyword being read or written by an end user.

7. A method as claimed in claim 1 wherein the step of determining keywords includes any combination of:

determining keywords of categories of content browsed by an end-user;

determining keywords of categories of content read by an end-user;

determining keywords of categories of content written by an end-user;

recency of keyword of category read or written by an end-user;

frequency of keyword of category read or written by an end-user;

determining keywords of tags of content browsed, read or written by an end-user;

frequence of keywords of tags read or written by an end-user; and

recency of keywords of tags read or written by an end-user.

8. A method as claimed in claim 7 further comprising any combination of the steps of:

expiring category keywords based on respective recency or frequency; and

expiring tag keywords based on respective recency or frequency.

9. In a global network of computers, a method of targeting advertisements, comprising the computer implemented steps of:

obtaining demographic information from end-users using on-line means;

monitoring end user activity and determining keywords therefrom;

receiving a subject advertisement having keywords associated therewith; and

determining end user to target the subject advertisement to based on a comparison of (i) a combination of determined end user activity keywords and obtained end-user demographic information to (ii) the subject advertisement keywords.

10. A method as claimed in claim 9 wherein the combination is advertiser defined.

11. A method as claimed in claim 9 further comprising the step of

obtaining bid amounts for projected audience reach where audience reach is estimated number of end-users the subject advertisement is determined to be targeted for.

12. A method as claimed in claim 11 wherein the step of obtaining bid amounts includes utilizing a graphical user interface having a user-controlled sliding view of estimated number of end-users viewing or selecting per day as graphed against cost per view.

13. A method as claimed in claim 11 wherein the step of obtaining bid amounts includes:

receiving input dollar amount per number of views, and

in response, indicating likely number of impressions resulting and average placement of the subject advertisement for the input dollar amount.

14. A method as claimed in claim 13 wherein the step of receiving input dollar amount is per number of sales completed or per registration completed.

15. A method as claimed in claim 11 wherein the step of obtaining bid amounts includes:

receiving input dollar amount per click-through, and

in response, indicating likely number of click-throughs resulting, average placement of the subject advertisement and total cost of the subject advertisement.

16. A method as claimed in claim 11 further comprising the step of prioritizing the subject advertisement relative to other advertisements in a manner based on financial reward to a hosting web site or ad serving network that makes determination of end-users to target advertisements to.

17. A method as claimed in claim 11 wherein the step of obtaining bid amounts employs a Vickrey style auction.

18. A method as claimed in claim 17 wherein the bid amounts are one of cost per click, cost per view or cost per acquisition made of item being advertised.

19. A method as claimed in claim 11 wherein the step of obtaining bid amounts includes focusing on a certain author or specific story for higher bid amounts.

20. In a global network of computers, a method of targeting and displaying advertisements to end-users comprising the computer implemented steps of:

obtaining demographic information from end-users;

monitoring end-user activity and determining keywords therefrom;

providing one or more advertisements having respective keywords associated therewith; and

displaying to a given end-user a subset of the advertisements as a function of advertisement keywords compared to any of the demographic information of the given end-user and/or given end-user activity keywords.

21. A method as claimed in claim 20 wherein the step of displaying includes selecting and ordering advertisements of the subset based on respective bid amounts of said advertisements.

22. A method as claimed in claim 20 further comprising the step of projecting respective likelihood of the given end-user selecting the advertisements in the subset, and

the step of displaying includes displaying said advertisements as a function of respective projected likelihood.

23. A method as claimed in claim 22 wherein the step of displaying includes ranking said advertisements as a function of respective projected likelihood multiplied by respective bid amount, and displaying to the given end user the advertisements in the subset according to said ranking.

24. A method as claimed in claim 23 wherein said ranking further includes degrading the respective projected likelihood of the given end-user selecting the advertisements in the subset every N times one of the advertisements is viewed by the given end-user and not selected by the end-user, N being greater than zero.

25. A method as claimed in claim 20 further comprising the step of reporting to advertisers indications of the advertisements displayed and selected by end-users.

26. A method as claimed in claim 25 wherein the step of reporting includes reporting to advertisers any combination of number of sales, number of subscriptions, number of registrations made by end-users through respective advertisements.

27. A method as claimed in claim 25 wherein the step of reporting includes filtering reports by demographics, keywords, category, context and/or end-user behavior.

28. A method as claimed in claim 25 wherein the step of reporting includes showing a breakdown on reports by demographics, keywords/phrase, category, context and/or end-user behavior.

29. A method as claimed in claim 20 further comprising the step of obtaining end-user ratings of the displayed advertisements.

30. A method as claimed in claim 29 wherein the step of obtaining is only from end-users who selected the displayed advertisement or end-users who made a purchase through the displayed advertisement.

31. A method as claimed in claim 20 wherein the advertisements are categorized by any of:

advertiser type, product type, geographic region, product cost range, language and keywords.

32. A method as claimed in claim 31 wherein the step of displaying includes displaying to the given end-user an option to view other similar advertisements based on categorization of the advertisements in the subset.

33. A method as claimed in claim 32 wherein upon end-user selection of the option, one or more similar advertisements are displayed and at least one advertisement of the subset of advertisements remains visible.

34. A method as claimed in claim 32 wherein said displaying an option includes

(i) enabling the end-user to respond to the other similar advertisements, or

(ii) for each similar advertisement, providing a respective option to display more advertisements similarly categorized.

35. A method as claimed in claim 32 further comprising the step of enabling advertisers to (i) bid additional money to prevent display of the option or (ii) pay a fee to remove display of the option.

36. A method as claimed in claim 20 wherein the subset of advertisements include advertisements that the given end-user has previously seen, advertisements that the given end user has responded to in the past being identified and having indications thereof recorded.

37. A method as claimed in claim 36 wherein the step of displaying includes providing to the given end user an option to see advertisements previously viewed or responded to by the him.

38. A method as claimed in claim 36 wherein the step of displaying advertisements that the given end-user has previously seen includes displaying indications of those advertisements that he has previously responded to.

39. A method as claimed in claim 36 further comprising enabling other users to see the advertisements that the given end-user has responded to in the past.

40. A method as claimed in claim 36 further comprising the step of enabling the given end-user to see advertisements that his friends, colleagues or other connections have responded to in the past.

41. A method as claimed in claim 36 further comprising enabling a user to see, aggregated in a single place, advertisements recently viewed by those linking to the user.

42. A method as claimed in claim 36 further comprising the step of sorting advertisements by popularity.

43. A method as claimed in claim 36 further comprising the step of enabling a user to sort advertisements previously viewed by another user or group, said sorting being by advertiser, product type, recency or frequency of viewing, or advertiser ranking or rating.

44. A method as claimed in claim 43 wherein a default sorting for the user is applied.

45. A method as claimed in claim 36 further comprising the step of enabling the given end-user to determine whether other users can see what advertisements he has viewed.

46. A method as claimed in claim 36 wherein the identified advertisements omit advertisements of a certain type.