Systems and Methods for the Semantic Modeling of Advertising Creatives in Targeted Search Advertising Campaigns

• US 20140257967A1
• Filed: 03/11/2013
• Published: 09/11/2014
• Est. Priority Date: 03/11/2013
• Status: Active Grant

• Current Assignee: Criteo Technology SAS (Criteo SA)
• Original Assignee: DataPop, Inc. (Criteo SA)
• Inventors: Zamanzadeh, Behzad, Zimmerman, John, Ramaksrihnan, Cartic
• Granted Patent: US 9,972,030 B2
• Time in Patent Office: Days
• US Class Current: 705/14.41
• CPC Class Codes: G06Q 30/0256 User search

Abstract

Systems and methods for the semantic modeling of advertising creatives included in targeted search advertising campaigns in accordance with embodiments of the invention are disclosed. In one embodiment, an advertising creative generation device includes a processor, an advertising creative generation application, at least one semantic model and performance data, wherein the an advertising creative generation application configures the processor to obtain a set of existing advertising creatives, where at least one of the existing advertising creatives comprises an existing concept, identify at least one existing advertising strategy pattern, determine performance data for the at least one existing advertising strategy pattern based on the performance data, identify at least one performance pattern based on the performance data for the at least one existing advertising strategy pattern, and generate at least one recommended advertising strategy.

Claims

1. An advertising creative generation device, comprising:

a processor;

a memory connected to the processor and configured to store an advertising creative generation application;

semantic model storage configured to store at least one semantic model comprising data describing relationships between advertising creatives, keywords, concepts described using categories and attribute-value pairs, and targeting data constituting a plurality of advertising strategy patterns; and

performance data storage configured to store performance data for advertising creatives, keywords, and targeting data comprising performance data for a plurality of advertising strategy patterns;

wherein the an advertising creative generation application configures the processor to;

obtain a set of existing advertising creatives, associated keywords, and advertising targets, where at least one of the existing advertising creatives comprises an existing concept;

identify at least one existing advertising strategy pattern by matching a relationship between the set of existing creatives, associated keywords and advertising targets with one of the set of advertising strategy patterns within the at least one semantic model;

determine performance data for the at least one existing advertising strategy pattern based on the performance data with respect to the advertising creative, keywords, and targeting data forming each of the at least one existing advertising strategy;

identify at least one performance pattern based on the performance data for the at least one existing advertising strategy pattern; and

generate at least one recommended advertising strategy based on the identified performance pattern and a subset of the set of existing advertising creatives, where at least one recommended advertising strategy comprises at least one updated concept based on the existing concept and the identified performance pattern.

2. The system of claim 1, wherein the performance data comprises campaign specific performance data for specific advertising creatives and associated keywords and targeting data.

3. The system of claim 2, wherein the performance data is selected from the group consisting of impressions, click-through rates, and conversion rates.

4. The system of claim 1, wherein the advertising creative generation application further configures the processor to generate advertising creatives based on the existing creatives and the at least one recommended advertising strategy.

5. The system of claim 4, wherein at least one of the generated advertising creatives modifies at least one of the existing creatives based on the at least one recommended advertising strategy.

6. The system of claim 4, wherein the advertising creative generation application further configures the processor to transmit the generated advertising creatives to a device selected from the group consisting of an advertising server system and a search engine provider.

7. The system of claim 1, wherein the advertising creative generation application further configures the processor to identify at least one performance pattern based on global performance data, where the global performance data includes performance data for advertising creatives, keywords, and targeting data comprising performance data for a plurality of advertising strategy patterns across a plurality of existing targeted search advertising campaigns.

8. The system of claim 7, wherein the advertising creative generation application further configures the processor to identify at least one performance pattern by performing a regression analysis based on the at least one existing advertising strategy pattern and the global performance data.

9. The system of claim 7, wherein the advertising creative generation application further configures the processor to generate at least one recommended advertising strategy that is not included in the at least one existing advertising strategy pattern and the global performance data.

10. The system of claim 1, wherein the advertising creative generation application further configures the processor to generate at least one recommended advertising strategy based on the identified performance pattern, a subset of the set of existing advertising creatives, and at least one of the at least one sematic model.

11. A method for generating advertising creatives, comprising:

obtaining a set of existing advertising creatives, associated keywords, and advertising targets using an advertising creative generation device, where at least one of the existing advertising creatives comprises an existing concept;

identifying at least one existing advertising strategy pattern by matching a relationship between the set of existing creatives, associated keywords and advertising targets with one of the set of advertising strategy patterns within the at least one semantic model using the advertising creative generation device;

determining performance data for the at least one existing advertising strategy pattern based on the performance data with respect to the advertising creative, keywords, and targeting data forming each of the at least one existing advertising strategy using the advertising creative generation device;

identifying at least one performance pattern based on the performance data for the at least one existing advertising strategy pattern using the advertising creative generation device; and

generating at least one recommended advertising strategy based on the identified performance pattern and a subset of the set of existing advertising creatives using the advertising creative generation device, where at least one recommended advertising strategy comprises at least one updated concept based on the existing concept and the identified performance pattern.

12. The method of claim 11, wherein the performance data comprises campaign specific performance data for specific advertising creatives and associated keywords and targeting data.

13. The method of claim 12, wherein the performance data is selected from the group consisting of impressions, click-through rates, and conversion rates.

14. The method of claim 11, further comprising generating advertising creatives based on the existing creatives and the at least one recommended advertising strategy using the advertising creative generation device.

15. The method of claim 14, wherein at least one of the generated advertising creatives modifies at least one of the existing creatives based on the at least one recommended advertising strategy.

16. The method of claim 14, further comprising transmitting the generated advertising creatives to a device using the advertising creative generation device, where the device is selected from the group consisting of an advertising server system and a search engine provider.

17. The method of claim 11, further comprising identifying at least one performance pattern based on global performance data using the advertising creative generation device, where the global performance data includes performance data for advertising creatives, keywords, and targeting data comprising performance data for a plurality of advertising strategy patterns across a plurality of existing targeted search advertising campaigns.

18. The method of claim 17, further comprising identifying at least one performance pattern by performing a regression analysis based on the at least one existing advertising strategy pattern and the global performance data using the advertising creative generation device.

19. The method of claim 17, further comprising generating at least one recommended advertising strategy that is not included in the at least one existing advertising strategy pattern and the global performance data using the advertising creative generation device.

20. The method of claim 11, further comprising generating at least one recommended advertising strategy based on the identified performance pattern, a subset of the set of existing advertising creatives, and at least one of the at least one sematic model using the advertising creative generation device.