CONTROLLING CONTENT DISTRIBUTION

• US 20110078000A1
• Filed: 09/24/2010
• Published: 03/31/2011
• Est. Priority Date: 09/25/2009
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Zhang, Fan, Ma, Sheng
• Application Number:
  US12/889,917
• Publication Number:
  US 20110078000A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements

Abstract

Distributing content using one or more content distributors associated with respective content distribution channels is based on an analysis of historical content distribution information and analysis rules. Recommended actions are provided to a content provider along with estimations of predicted results.

Claims

1. A method for distributing content comprising:

receiving, in a content manager, content distribution information regarding how content is to be distributed;

automatically analyzing historical data stored in a storage device accessible by the content manager, the analyzing comprising;

normalizing the historical data to obtain a performance metric,

categorizing the performance metric to obtain metric driver value,

transforming the metric driver value to a recommended action regarding a content distribution setting, and

estimating a predicted result of accepting the recommended action;

adjusting the content distribution information based on the analysis of the historical data; and

distributing content based on the adjusted content distribution information.

2. The method of claim 1, wherein the content distribution information comprises information regarding a content distribution channel and content distribution control settings for a content distribution system associated with the content distribution channel, and wherein adjusting the information comprises adjusting at least one content distribution control setting for the content distribution system.

3. The method of claim 1, further comprising generating recommendation information regarding a recommended adjustment of the content distribution information based on the analysis of the historical data.

4. The method of claim 3, wherein adjusting the content distribution information comprises adjusting the content distribution information based on the recommended adjustment.

5. The method of claim 3, further comprising providing the recommendation information to a user and receiving approved adjustment information from the user, wherein adjusting the content distribution information comprises adjusting the content distribution information based on the approved adjustment information.

6. The method of claim 3, wherein the recommendation information comprises information regarding adjustment of a content distribution setting associated with a content distribution system.

7. The method of claim 3, wherein the recommendation information comprises information regarding adjustment of a content distribution channel.

8. The method of claim 1, further comprising receiving rule authoring information from a user and creating a custom rule according to the rule authoring information, wherein analyzing the historical data comprises analyzing the historical data based on the custom rule.

9. The method of claim 8, wherein creating the custom rule comprises adjusting a default rule.

10. The method of claim 1, wherein adjusting the content distribution information comprises modifying at least one of content bid information and content budget information based on the recommended setting.

11. The method of claim 10, wherein analyzing the historical data further comprises converting a current content distribution setting to a recommended content distribution setting based on the recommended action, wherein estimating a predicted result comprises estimating a performance metric predicted to result from distributing content based on the recommended setting.

12. A method for advertising comprising:

receiving, in an advertisement distribution manager, advertisement information comprising advertisement channel information and channel setting information;

analyzing, by the advertisement distribution manager, historical advertisement information based on rules selected from a rule repository, the rules being selected from among default rules and customized rules, the rules being selected based on the advertisement channel information, wherein analyzing includes normalizing the historical advertisement information to obtain a performance metric, transforming the performance metric to recommendation information regarding a recommended channel setting, and estimating a predicted result of accepting the recommendation information; and

automatically outputting, by the advertisement distribution manager, the recommendation information regarding a recommended channel setting.

13. A method for managing advertisement distribution comprising:

storing advertisement distribution rule information on a storage device to create an advertisement distribution rule library, each rule being associated with at least one advertisement distribution channel;

receiving advertisement distribution information regarding distribution of at least one advertisement, the distribution information being associated with a user and comprising information regarding at least one distribution channel;

analyzing advertisement distribution history data using rules selected from the advertisement rule library based on the advertisement distribution information; and

providing, to the user, adjustment information based on the analysis, the adjustment information comprising a recommended distribution setting of a distribution system associated with the advertisement distribution information.

14. The method of claim 13, wherein analyzing the advertisement distribution history data comprises analyzing advertisement distribution history data for at least one advertisement associated with the user.

15. The method of claim 14, wherein analyzing the advertisement distribution history data further comprises analyzing advertisement distribution history data for an advertisement distribution channel.

16. The method of claim 14, further comprising creating a custom rule associated with a user, and including advertisement distribution rule information associated with the custom rule in the rule library, wherein analyzing advertisement distribution history data uses the custom rule.

17. A content distribution management system comprising:

an analysis rule library repository including rules regarding analysis of content distribution information;

a user data repository; and

a content distribution analyzer computer processor comprising;

an analysis pipeline configured to analyze content distribution history data according to selected rules of the rule library repository, the selected rules being selected based on information of the user data repository, wherein the analysis of the content distribution history data includes normalizing the historical data to obtain a performance metric, transforming the performance metric to a recommended action regarding a content distribution setting, estimating a predicted result of accepting the recommended action, and outputting the recommended action.

18. The content distribution management system of claim 17, further comprising a rule authoring computer processor operable to create a rule in the rule library for use in analyzing content distribution history data.

19. The content distribution management system of claim 17, wherein the analysis pipeline of the content distribution analyzer computer processor is further configured to modify at least one of content bid information and content budget information based on the recommended setting.

20. The content distribution management system of claim 19, wherein the analysis pipeline of the content distribution analyzer computer processor is further configured to change a current content distribution setting to a recommended content distribution setting based on the recommended action, and to estimate a performance metric predicted to result from distributing content based on the recommended setting.