IP Library Granted Patent US 9,691,083
Granted Patent B2
US 9,691,083 · App. 13/934,109 · Granted Jun 27, 2017

Opportunity identification and forecasting for search engine optimization

Inventors: Jimmy Yu (Foster City, CA); Sammy Yu (San Mateo, CA); Lemuel S. Park (Cerritos, CA); Rolland Yip (Ma On Shan, HK)
Assignee: BRIGHTEDGE TECHNOLOGIES, INC.
G06Q30/0256G06F17/30864G06N99/00
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Quick Facts
Patent No.
US 9,691,083
App. No.
13/934,109
Granted
Jun 27, 2017
Kind
B2
Abstract

A method of optimizing placement of references to an entity includes identifying at least search term to be optimized, determining a score for results of a search of a network with respect to the entity, determining costs associated with improving the score, and determining values associated with improving the score.

Claims (48)

1. A method of placement of references to an entity in one or more channels unassociated with paid advertisements, the method performed by a processor, the method comprising:

identifying at least one search term to be optimized for one or more channels unassociated with paid advertisements;

searching a network using the at least one search term to generate search results that include at least one reference to an entity that are unassociated with paid advertisements;

determining a score for the reference to the entity that are unassociated with paid advertisements;

determining costs associated with improving the score for the reference;

determining a value for the search term by correlating two or more of the score for the reference, the costs associated with improving the score for the reference, and revenue associated with improving the score for the reference;

determining a conversion rate for visits to a website of the entity through the reference to the entity with the search terms that directed the visits to the entity; and

correlating at least the conversion rate for visits to the website and the score for the reference to the entity to identify one or more of the at least one search term.

2. The method of claim 1 , wherein the value for the search term is determined by correlating two or more of the score for the reference, the costs associated with improving the score for the reference, the conversion rate, revenue associated with improving the score for the reference, and revenue associated with conversions for the reference.

3. The method of claim 1 , wherein the reference to the entity includes one or more of: news items, social media items, social network items, social news items, or organic references associated with the entity.

4. The method of claim 1 , wherein the one or more channels includes organic searches, page searches, e-mail, blogs, social networks, social news, affiliate marketing, forums, news sites, rich media, and social bookmarks.

5. The method of claim 1 , further comprising:

scoring references unassociated with the entity and associated with the search term to generate scores for the references unassociated with the entity within the search results; and

when the scores of the references to the entity are lower than the scores for the references unassociated with the entity, targeting the search terms in a paid search.

6. The method of claim 1 , further comprising providing the value for the search term for display.

7. A method for optimizing online references to an entity that are non-paid advertisements, the method performed by a processor, the method comprising:

searching at least one channel unassociated with paid advertisements on a network for references to the entity unassociated with paid advertisements using a plurality of search terms to generate search results that include a plurality of references;

scoring the references to the entity associated with each of the plurality of search terms from the plurality of references to generate scores for the references to the entity;

determining a conversion rate for visits to a website of the entity through the reference with the search terms that directed the visits to the entity;

correlating at least the conversion rate for visits to the website and the scores for the references to the entity to identify one or more of the plurality of search terms; and

for the identified one or more of the plurality of search terms, forecasting an increase in conversions for the references to the entity associated with an increase in the scores for the references to the entity.

8. The method of claim 7 , wherein searching the at least one channel includes searching at least one of: organic searches, page searches, e-mail, blogs, social networks, social news, affiliate marketing, discussion forums, news sites, rich media, and social bookmarks.

9. The method of claim 7 , wherein using the plurality of search terms to generate search results includes using a plurality of keywords and crawling previously returned search results and conducting a keyword frequency analysis to identify at least some of the plurality of keywords.

10. The method of claim 7 , further comprising providing the identified one or more of the plurality of search terms for display.

11. The method of claim 7 , further comprising providing the forecasted increase in conversions for the references to the entity for display.

12. The method of claim 7 , wherein scoring the references to the entity associated with each of the plurality of search terms includes determining a keyword rank.

13. The method of claim 7 , further comprising:

scoring references unassociated with the entity and associated with each of the plurality of search terms to generate scores for the references unassociated with the entity within the search results; and

when the scores of the references to the entity are lower than the scores for the references unassociated with the entity, targeting the search terms in a paid search.

14. The method of claim 7 , further comprising:

crawling the search results to determine additional search terms;

searching the at least one channel unassociated with paid advertisements on the network using the additional search terms to generate additional search results;

determining scores for references to the entity and for references to an additional entity included in the additional search results;

analyzing the scores for the references to the entity and for the references to the additional entity to determine if the entity ranks with respect to the additional search terms and if the additional entity ranks with respect to the additional search terms; and

targeting the search terms in a paid search if the additional entity ranks above a first threshold score and the entity ranks below a second threshold score.

15. A non-transitory computer readable storage medium configured to cause a system to perform operations of optimizing online references to an entity that are non-paid advertisements, the operations comprising:

searching at least one channel unassociated with paid advertisements on a network for references to the entity unassociated with paid advertisements using a plurality of search terms to generate search results that include a plurality of references;

scoring the references to the entity associated with each of the plurality of search terms from the plurality of references to generate scores for the references to the entity;

determining a conversion rate for visits to a website of the entity through the reference with the search terms that directed the visits to the entity;

correlating at least the conversion rate for visits to the website and the scores for the references to the entity to identify one or more of the plurality of search terms; and

for the identified one or more of the plurality of search terms, forecasting an increase in conversions for the references to the entity associated with an increase in the scores for the references to the entity.

16. The non-transitory computer readable storage medium of claim 15 , wherein searching the at least one channel includes searching at least one of: organic searches, page searches, e-mail, blogs, social networks, social news, affiliate marketing, discussion forums, news sites, rich media, and social bookmarks.

17. The non-transitory computer readable storage medium of claim 15 , wherein using the plurality of search terms to generate search results includes using a plurality of keywords and crawling previously returned search results and conducting a keyword frequency analysis to identify at least some of the plurality of keywords.

18. The non-transitory computer readable storage medium of claim 15 , wherein the operations further comprise providing the identified one or more of the plurality of search terms for display.

19. The non-transitory computer readable storage medium of claim 15 , wherein the operations further comprise providing the forecasted increase in conversions for the references to the entity for display.

20. The non-transitory computer readable storage medium of claim 15 , wherein the operations further comprise:

scoring references unassociated with the entity and associated with each of the plurality of search terms to generate scores for the references unassociated with the entity within the search results; and

when the scores of the references to the entity are lower than the scores for the references unassociated with the entity, targeting the search terms in a paid search.

Assignments (3)
SECURITY INTEREST Recorded Feb 24, 2026
From: BRIGHTEDGE TECHNOLOGIES, INC.
To: WESTERN ALLIANCE BANK
Reel/Frame 073881/0147 →
SECURITY INTEREST Recorded Nov 25, 2024
From: BRIGHTEDGE TECHNOLOGIES, INC.
To: STIFEL BANK
Reel/Frame 069399/0371 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 20, 2013
From: YU, JIMMY; YU, SAMMY; PARK, LEMUEL S.; YIP, ROLLAND
To: BRIGHTEDGE TECHNOLOGIES, INC.
Reel/Frame 031046/0474 →
Continuity (2)
Continuation 12854644 · Aug 11, 2010
Related Publication 20130332278A1 · Dec 12, 2013