TOOL FOR OPTIMIZING ADVERTISING ACROSS DISPARATE ADVERTISING NETWORKS

• US 20080103953A1
• Filed: 05/25/2007
• Published: 05/01/2008
• Est. Priority Date: 10/25/2006
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Lanman, Richard Burnham, Biggs, Jody D., Flake, Gary W., Meek, Christopher A., Brewer, Brett D., Burdick, Brian, Dominowska, Ewa, Chickering, David Max
• Application Number:
  US11/753,790
• Publication Number:
  US 20080103953A1
• Time in Patent Office: Days
• US Class Current: 705/37
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

An optimization tool is provided for individual participants who participate in multiple online advertising environments wherein the tool interfaces with the multiple environments in an optimal manner on behalf of the individual participants. A participant using the tool can specify goals and/or constraints for participating in one or more of the networks, and then the tool automatically optimizes advertising expenditure for advertising transactions across the different networks. The tool also tracks the performance of the participant across the different networks and dynamically tunes the participant'"'"'s advertising expenditure based on such performance as well as the changing conditions of the marketplace.

Claims

1. A method of facilitating trading of advertising for an advertiser in multiple disparate advertising networks, comprising:

receiving information about asks from at least one publisher for at least one advertisement space placed on at least one advertising network of a plurality of disparate advertising networks;

receiving at least one objective for bidding for the at least one advertisement space placed on the at least one advertising network; and

based on the at least one objective, analyzing the asks from the at least one publisher for the at least one advertisement space across the disparate advertising networks and automatically optimizing the bidding for the at least one advertisement space on behalf of the advertiser.

2. The method of claim 1, wherein said optimizing includes optimizing the bidding for the at least one advertisement space taking into account performance data about past transactions.

3. The method of claim 1, wherein said optimizing includes optimizing the bidding for the at least one advertisement space taking into account dynamically changing market conditions represented by the at least one advertising network.

4. The method of claim 1, further comprising:

translating the at least one objective to different expressions corresponding to on the different advertising networks.

5. The method of claim 1, wherein the receiving of the at least one objective includes receiving a specification of at least one constraint on the at least one objective.

6. The method of claim 1, further comprising:

disabling bidding with respect to a designated advertising network of the plurality of advertising networks.

7. The method of claim 1, further comprising:

enabling bidding with respect to a designated new advertising network in addition to the plurality of advertising networks.

8. The method of claim 1, further comprising:

completing at least one transaction based on the optimized bidding for the at least one advertisement space.

9. The method of claim 8, further comprising:

waiting for confirmation of the at least one transaction prior to said completing.

10. A tool to facilitate trading of advertising for an advertising entity in multiple disparate advertising networks, comprising:

an input component for receiving input from the advertising entity about at least one objective for advertising transactions across the different advertising networks; and

an analysis engine that optimizes advertising expenditure of the advertising entity across the different advertising networks based on the at least one objective.

11. The tool of claim 10, wherein the input component receives a specification of a function of the quality of advertising involved in advertising transactions, and wherein the analysis engine optimizes advertising expenditure of the advertising entity based on the function.

12. The tool of claim 10, wherein the input component receives a specification of a function of the size of other participants in advertising transactions involved in advertising transactions, and wherein the analysis engine optimizes advertising expenditure of the advertising entity based on the function.

13. The tool of claim 10, wherein the input component receives a specification of a function of display characteristics of the publishing inventory involved in advertising transactions, and wherein the analysis engine optimizes advertising expenditure of the advertising entity based on the function.

14. The tool of claim 10, wherein the input component receives a specification of a function of the relevance of advertising involved in advertising transactions involved in advertising transactions, and wherein the analysis engine optimizes advertising expenditure of the advertising entity based on the function.

15. The tool of claim 10, wherein the input component receives a specification of a function of a performance metric of advertising or publishing inventory involved in advertising transactions involved in advertising transactions, and wherein the analysis engine optimizes advertising expenditure of the advertising entity based on the function.

16. The tool of claim 10, wherein the analysis engine optimizes the advertising entity'"'"'s bids for advertisement space by taking into account performance data about past transactions by the advertising entity in the different advertising networks.

17. The tool of claim 10, wherein the analysis engine optimizes the advertising entity'"'"'s bids for advertisement space taking into account dynamically changing market conditions represented by the different advertising networks.

18. The tool of claim 10, wherein the input component receives at least one constraint on the at least one objective and the analysis engine optimizes advertising expenditure of the advertising entity across the different advertising networks based on the at least one objective and the at least one constraint on the at least one objective.

19. A method of facilitating trading of advertising for an individual publisher in multiple disparate advertising networks, comprising:

analyzing performance data associated with results of transactions conducted in the multiple disparate advertising networks; and

specifying at least one objective for asking for at least one advertisement space placed on the at least one advertising network by the publisher; and

based on the at least one objective, on behalf of the publisher, optimizing asks for the at least one advertisement space across the different advertising networks based on the analyzing.

20. The method of claim 19, further comprising:

analyzing changes in market conditions of the multiple disparate advertising networks; and

optimizing asks on behalf of the publisher across the different advertising networks based on the analyzing of the changes in market conditions.