Granted Patent B1

US 12,243,075 · App. 18/202,844 · Granted Mar 4, 2025

Inventors: Yugang Hu (Salt Lake City, UT); Seth Moore (Lehi, UT); JP Knab (Riverton, UT); Amit Goyal (South Jordan, UT)

Assignee: Overstock.com, Inc.

G06Q30/0256

Abstract

Claims (58)

1. A method for determining the online exposure of a target webpage in search results, said method comprising:

causing a content optimization server to receive source code from each of a plurality of proxy computers located throughout a geographic region through an online server, each defining a search results page from one of the plurality of proxy computers located throughout the geographic region, wherein the content optimization server comprises at least a processor;

processing the source code from each of the plurality of proxy computers with the processor of the content optimization server to identify target source code in the source code for each of the plurality of proxy computers, wherein the content optimization server identifies blocks of target source code by matching text in the source code to predetermined code in the server;

causing the content optimization server to parse one or more blocks of source code, each containing the target source code, wherein the parsed target source code includes at least some of the source code that defines target content displayed on the target webpage and used to identify the target webpage on the search results page;

causing the processor of the content optimization server to determine a relative metric for each parsed block of target source code from each of the plurality of proxy computers by causing the processor of the content optimization server to determine the location of target content on the search results page by determining the distance of the target content from a predetermined location on the search results page;

determining an overall relative metric as a measure of the online exposure of the target webpage in search results with the processor of the content optimization server by averaging the relative metric from each of the plurality of proxy computers;

using the processor of the content optimization server to dynamically update the overall relative metric according to a selected schedule; and

storing the relative metric in a database.

2. A system for determining the online exposure of a target webpage in search results, said system comprising:

a processor;

a memory coupled to the processor; and

computer-readable instructions stored in the memory that, when executed by the processor, cause the processor to: (i) receive source code defining a search results page from a web server from each of a plurality of proxy computers located throughout a geographic region through an online server, (ii) identify a target source code block in the source code for each of the plurality of proxy computers by matching text in the source code to predetermined code stored in the server, the target source code block defining, at least partially, target content on the target webpage, (iii) identify HTML tags specifying where target content starts and ends on the search results page for each of the plurality of proxy computers, (iv) determine the distance of the target content from a predetermined location on the search results page for each of the plurality of proxy computers, (v) determine a relative metric for the target content for each of the plurality of proxy computers based on the distance of the target content from a predetermined location on the search results page, (vi) average the relative metric for each of the plurality of proxy computers located throughout a geographic region to determine an overall relative metric as a measure of the online exposure of the target webpage in search results, (vii) store the overall relative metric in a database, and (viii) dynamically update the overall relative metric according to a selected schedule.

3. A method for analyzing a webpage, said method comprising;

causing a content optimization server to receive source code from an online server defining the webpage from each of a plurality of proxy computers located throughout a geographic region, wherein the content optimization server comprises at least a processor;

using the processor of the content optimization server to process the source code from each of the plurality of proxy computers located throughout a geographic regions to identify target source code in the source code from each of the plurality of proxy computers located throughout the geographic region, wherein the content optimization server identifies blocks of target source code by matching text in the source code to predetermined code in the server, the target source code defining, at least partially, a search result on the webpage;

causing the content optimization server to parse one or more blocks of source code, each containing the target source code, wherein the parsed target source code includes at least some of the source code that defines the search results on the webpage;

processing the parsed target source code from each of the plurality of proxy computers located throughout a geographical region with the processor of the content optimization server, by causing the processor of the content optimization server to generate a relative metric as a measure of the online exposure of the target source code for each of the plurality of proxy computers located throughout the geographic region by causing the processor of the content optimization server to determine the location of target content on the webpage by determining the distance of the target content from a predetermined location on the webpage;

determining an overall relative metric as a measure of the online exposure of the target source code in search results with the processor of the content optimization server by averaging the relative metric from each of the plurality of proxy computers using the processor of the content optimization server to determine an overall relative metric as a measurement of the online exposure of the target source code in search results;

using the processor of the content optimization server to dynamically update the relative metric according to a selected schedule; and

storing the relative metric in a database.

4. The method of claim 1 , wherein causing the processor of the content optimization server to determine a relative metric for each parsed block of target source code from each of the plurality of proxy computers also comprises:

determining whether the target content is visible to the user when first seeing the search results page.

5. The method of claim 4 , wherein causing the processor of the content optimization server to determine a relative metric for each parsed block of target source code from each of the plurality of proxy computers also comprises:

determining whether the target content is visible to the user when first seeing the search results page; and

determining the size of the visible target content relative to the size of the initially visible area of the search results page.

6. The method of claim 1 wherein the relative metric is based on at least the location of the target content on the search results page.

7. The method of claim 6 wherein the relative metric is further based on the size of the target content with respect to the size of the search results page, whether the target content is visible to the user when first seeing the search results page, and the size of the target content visible to the user relative to the size of the initially visible part of the search results page.

8. The method of claim 1 also comprising:

automatically generating a bid amount for the target content to be displayed on the search results page according to the relative metric;

automatically changing the bid amount based on the dynamic updating of the relative metric; and

recommending a change in expenditure for the target content based on the bid amount.

9. The method of claim 8 , further comprising adjusting an advertising expenditure for online advertising based on the relative metric.

10. The method of claim 1 , further comprising:

fetching a keyword from a database;

forming a search query using the keyword on a search request webpage generated by a search engine server; and

causing the search engine server to perform a search using the keyword;

wherein the search results page contains the search results for the keyword.

11. The system of claim 2 , wherein computer-readable instructions stored in the memory cause the processor to determine the location of the target content on the search results page by using HTML tags specifying where target content starts and ends on the search results page and determining the distance of the target content from a predetermined location on the search results page.

12. The system of claim 11 , wherein the computer-readable instructions stored in the memory cause the processor to further:

determine whether the target content is visible to the user when first seeing the search results page; and

determine the size of the visible target content relative to the size of the initially visible area of the search results page.

13. The system of claim 2 wherein the relative metric is based on at least the location of the target content on the search results page.

14. The system of claim 13 wherein the relative metric is further based on whether the target content is visible to the user when first seeing the search results page, and the size of the target content visible to the user relative to the size of the initially visible part of the search results page.

15. The system of claim 2 wherein the computer-readable instructions stored in the memory additionally cause the processor to:

automatically generate a bid amount for the target content to be displayed on the search results page according to the relative metric;

automatically change the bid amount based on the dynamic updating of the relative metric; and

recommend a change in expenditure for the target content based on the bid amount.

16. The method of claim 3 , wherein causing the processor of the content optimization server to determine a relative metric for each parsed block of target source code from each of the plurality of proxy computers also comprises:

determining whether the target content is visible to the user when first seeing the webpage.

17. The method of claim 16 , wherein causing the processor of the content optimization server to determine a relative metric for each parsed block of target source code from each of the plurality of proxy computers also comprises:

determining whether the target content is visible to the user when first seeing the webpage on each of a plurality of proxy computers located throughout a geographic region; and

determining the size of the visible target content relative to the size of the initially visible area of the webpage on each of the plurality of proxy computers located throughout the geographic region.

18. The method of claim 3 wherein the relative metric is based on at least the distance of the target content from a given point on the webpage.

19. The method of claim 18 wherein the relative metric is further based on whether the target content is visible to a user of each of a plurality of proxy computers located throughout a geographic region when first seeing the webpage, and the size of the target content visible to a user of each of a plurality of proxy computers located throughout a geographic region relative to the size of the initially visible part of the webpage.

20. The method of claim 3 also comprising:

automatically generating a bid amount for the target content to be displayed on the webpage according to the relative metric;

automatically changing the bid amount based on the dynamic updating of the relative metric; and

recommending a change in expenditure for the target content based on the bid amount.

Assignments (1)

Continuity (2)

References Cited (400)