Online ad detection and ad campaign analysis

Patent metadata

Field	Value
Publication number	US-10891632-B2
Application number	US-201715806091-A
Country	US
Kind code	B2
Filing date	Nov 7, 2017
Priority date	Dec 11, 2008
Publication date	Jan 12, 2021
Grant date	Jan 12, 2021

Abstract

Metrics for online ads are captured by parsing web pages to identify ad beacons containing information identifying whether the online ads are for a particular client. These metrics are used to determine key performance indicators for auditing and competitor analysis for an online ad campaign.

First claim

What is claimed is:

1. A system comprising:
a processor;
a memory storing machine readable instructions that when executed by the processor cause the processor to:
scan, by a plurality of scan servers located at different geographical locations, a plurality of web sites based on a competitor analysis of a set of competitors of a client;
detect web pages based on the scanning of the plurality of web sites;
parse the web pages of the plurality of web sites;
identify ad beacons from the parsed web pages;
determine, based on an analysis of information that describes online ads for the client and an analysis of the ad beacons, whether the ad beacons identify the online ads for the client;
determine metrics for the online ads for the client identified by the ad beacons;
determine delivery quality of the identified online ads from a set of the metrics by analyzing, from the set of the metrics, frequency of an occurrence of specified content in the identified online ads based on a specified scan frequency that corresponds to the specified content;
determine key performance indicators (KPIs) from the metrics, wherein the KPIs are configured to determine effectiveness of ads relative to content and web sites;
perform a cost analysis for the identified online ads, by analyzing, from the KPIs, actual placement that includes an actual vertical and horizontal placement location of the identified online ads on a web page and relative to the web page, versus planned placement that includes a planned vertical and horizontal placement location of the identified online ads on the web page and relative to the web page;
modify, based on the determined delivery quality of the identified online ads and the KPIs, a number of the identified online ads for at least one of the web pages by
modifying, by at least one scan server of the plurality of scan servers, the number of the identified online ads to modify the at least one of the web pages to increase or decrease the number of the identified online ads; and

a network interface to communicate with web servers hosting the plurality of web sites operable to include the online ads for the client.

2. The system according to claim 1 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
utilize the information that describes the online ads for the client to distinguish the online ads for the client or the client's competitors from other online ads.

3. The system according to claim 1 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
determine, based on the information, whether the ad beacons identify the online ads for the client by comparing a unique client ID to an ad beacon URL.

4. The system according to claim 1 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
generate a display of attributes for the identified online ads for the client and for competitor ads, the metrics for the identified online ads for the client and for the competitors ads, and the KPIs; and
implement, in the generated display, dynamic searching of advertising statistics, and selected KPIs.

5. The system according to claim 1 , wherein the machine readable instructions to scan the plurality of web sites, further comprise machine readable instructions that when executed by the processor further cause the processor to:
scan the plurality of web sites based on a region-based scan for online ad information.

6. The system according to claim 1 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
generate a competitor analysis report based on the competitor analysis, wherein the competitor analysis report is generated by analyzing metrics for competitors to identify which competitors are advertising and where and how often the competitors are advertising.

7. The system according to claim 1 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
determine whether an identified ad beacon of the identified ad beacons includes a click thru URL.

8. The system according to claim 7 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
follow the click thru URL until a URL is found that does not match an ad beacon or a click thru URL; and
store the metrics for each click thru URL or ad beacon identified when following the click thru URL.

9. The system according to claim 1 , further comprising machine readable instructions that when executed by the processor further cause the processor to:
determine a location on the at least one of the plurality of web sites to increase or decrease the number of the client's ads.

10. A computer implemented method comprising:
scanning, by a plurality of scan servers located at different geographical locations, a plurality of web sites;
detecting web pages based on the scanning of the plurality of web sites;
parsing the web pages of the plurality of web sites;
identifying ad beacons from the parsed web pages;
determining, based on an analysis of information that describes online ads for a client, whether the ad beacons identify the online ads for the client;
determining, by a processor, metrics for the identified online ads for the client;
determining key performance indicators (KPIs) which identify effectiveness of ads relative to content and web sites;
performing a cost analysis for the identified online ads, by analyzing, from the KPIs, actual placement that includes an actual vertical and horizontal placement location of the identified online ads on a web page and relative to the web page, versus planned placement that includes a planned vertical and horizontal placement location of the identified online ads on the web page and relative to the web page; and
determining, based on the KPIs and an analysis of locations of the web pages in their web site hierarchies for websites of the plurality of web sites that include at least three web pages, and the web pages according to their locations in their web site hierarchies, a location on the at least one of the plurality of web sites to increase or decrease, for at least one of the web pages, a number of the identified online ads for the client by
modifying, by at least one scan server of the plurality of scan servers, the number of the identified online ads to modify the at least one of the web pages to increase or decrease the number of the identified online ads.

11. The computer implemented method of claim 10 , wherein the information comprises information unique to the client or the client's competitors, further comprising:
analyzing the information to distinguish the online ads of the client or the client's competitors from other online ads.

12. The computer implemented method of claim 10 , further comprising:
determining, based on the information, whether the ad beacons identify the online ads for the client by comparing a unique client ID to an ad beacon URL.

13. The computer implemented method of claim 10 , further comprising:
generating reports including the KPIs, wherein the reports include a competitor analysis report which is generated by analyzing the metrics for the client's competitors to identify which competitors are advertising and where and how often the competitors are advertising.

14. A non-transitory computer readable medium having stored thereon machine readable instructions, the machine readable instructions

Assignees

• Accenture Global Services Ltd

Inventors

• Kirkby Stephen Denis
• Kellett Peter
• Figg Matthew
• Holman Jarred

Classifications

• G06Q30/0275

  Auctions · CPC title

• G06Q30/02 Primary

  Marketing; Price estimation or determination; Fundraising · CPC title

• G06Q30/0242

  Determining effectiveness of advertisements · CPC title

• G06Q10/10

  Office automation; Time management · CPC title

• G06Q30/0277

  Online advertisement · CPC title