IP Library Patent Application 12856565
Patent Application
App. No. 12/856,565

LEARNING SYSTEM FOR THE USE OF COMPETING VALUATION MODELS FOR REAL-TIME ADVERTISEMENT BIDDING

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Quick Facts
Patent No.
US None
App. No.
12/856,565
Abstract

In embodiments of the present invention, improved capabilities are described for using a plurality of competing economic valuation models to predict an economic valuation for each of a plurality of advertisement placements, advertisements, and advertisement-advertisement placement combinations, in response to receiving a request to place an advertisement. The economic valuation model may be based at least in part on real-time event data, historic event data, user data, third-party commercial data historical advertisement impressions, advertiser data, ad agency data, historical advertising performance data, and machine learning. Further, a computer program product, based on the methods and systems of the present invention, may evaluate each economic valuation produced by each of the plurality of competing economic valuation models to select one as a current valuation of an advertisement placement, advertisement, and/or advertisement-advertisement placement combination.

Claims (41)

1 . A computer program product embodied in a computer readable medium that, when executing on one or more computers, performs the steps of:

in response to receiving a request to place an advertisement, deploying a plurality of competing economic valuation models to predict an economic valuation for each of the plurality of advertisement placements; and

evaluating each valuation produced by each of the plurality of competing economic valuation models to select one as a current valuation of an advertising placement.

2 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on real time event data.

3 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on historic event data.

4 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on user data.

5 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on third-party commercial data.

6 . The computer program product of claim 1 , wherein the third party commercial data includes financial data relating to historical advertisement impressions.

7 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on contextual data.

8 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on advertiser data.

9 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on ad agency data.

10 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on historical advertising performance data.

11 . The computer program product of claim 1 , wherein the economic valuation model is based at least in part on machine learning.

12 . A computer program product embodied in a computer readable medium that, when executing on one or more computers, performs the steps of:

in response to receiving a request to place an advertisement, deploying a plurality of competing economic valuation models to predict an economic valuation for each of a plurality of combinations of advertisement placements and advertisements;

evaluating each valuation produced by each of the plurality of competing economic valuation models to select one as a first valuation of a combination of an advertising placement and an advertisement;

reevaluating each valuation produced by each of the plurality of competing economic valuation models to select one as a revised valuation for the combination of the advertising placement and the advertisement, wherein the revised valuation is based at least in part on analysis of an economic valuation model using real-time event data that was not available at the time of selecting the first valuation; and

replacing the first valuation with the second revised valuation for use in deriving a recommended bid amount for the combination of the advertising placement and the advertisement.

13 . Further comprising the computer program product of claim 12 , wherein the request is received from a publisher and the recommended bid amount is automatically sent to the publisher.

14 . Further comprising the computer program product of claim 12 , wherein the request is received from a publisher and a bid equaling the recommended bid amount is automatically placed on behalf of the publisher.

15 . Further comprising the computer program product of claim 12 , wherein the recommended bid amount is associated with a recommended time of ad placement.

16 . Further comprising the computer program product of claim 12 , wherein the recommended bid amount is further derived by analysis of a real-time bidding log that is associated with a real-time bidding machine.

17 . A computer program product embodied in a computer readable medium that, when executing on one or more computers, performs the steps of:

in response to receiving a request to place an advertisement, deploying a plurality of competing economic valuation models to evaluate information relating to a plurality of available combinations of a plurality of advertisement placements and a plurality of advertisements to predict an economic valuation for each combination of the plurality of advertisement placements and the plurality of advertisements; and

evaluating each valuation produced by each of the plurality of competing economic valuation models to select one valuation as a future valuation of a combination of an advertising placement and an advertisement.

18 . A computer program product embodied in a computer readable medium that, when executing on one or more computers, performs the steps of:

in response to receiving a request to place an advertisement, deploying a plurality of competing economic valuation models to evaluate information relating to a combination of a plurality of available advertisement placements and a plurality of advertisements to predict an economic valuation for each combination of the plurality of advertisement placements and the plurality of advertisements; and

evaluating, in real time, each valuation produced by each of the plurality of competing economic valuation models to select one valuation as a future valuation for the combination of an advertising placement and an advertisement.

19 . Further comprising the computer program product of claim 17 , wherein the future valuation is based at least in part on simulation data describing a future event.

20 . Further comprising the computer program product of claim 12 , wherein the future event is a stock market fluctuation.

21 . Further comprising the computer program product of claim 12 , wherein the simulation data describing future event is derived from analysis of historical event data that is chosen based at least in part on contextual data relating to an advertisement to be placed in the advertising placement.

22 . A computer program product embodied in a computer readable medium that, when executing on one or more computers, performs the steps of:

in response to receiving a request to place an advertisement, deploying a plurality of competing real-time bidding algorithms relating to a combination of a plurality of available advertisement placements and a plurality of advertisements to bid for advertisement placements; and

evaluating each bidding algorithm to select a preferred algorithm.

23 . The computer program product of claim 22 , wherein the competing real-time bidding algorithms use data from a real-time bidding log.

24 . A computer program product embodied in a computer readable medium that, when executing on one or more computers, performs the steps of:

in response to receiving a request to place an advertisement, deploying a plurality of competing real-time bidding algorithms relating to a combination of a plurality of available advertisement placements and a plurality of advertisements to bid for advertisement placements;

evaluating each bid recommendation created by the competing real-time bidding algorithms;

reevaluating each bid recommendation created by the competing real-time bidding algorithms to select one as a revised bid recommendation, wherein the revised bid recommendation is based at least in part on a real-time bidding algorithm using real-time event data that was not available at the time of selecting the bid recommendation; and

replacing the bid recommendation with the revised bid recommendation for use in deriving a recommended bid amount for a combination of an advertising placement and an advertisement.

25 . The computer program product of claim 24 , wherein the replacement occurs in real-time relative to the receipt of the request to place an advertisement.

Assignments (6)
TERMINATION AND RELEASE OF INTELLECTUAL PROPERTY SECURITY AGREEMENT (REEL/FRAME 051300/0931) Recorded Feb 22, 2023
From: MORGAN STANLEY SENIOR FUNDING, INC.
To: ROKU, INC.; ROKU DX HOLDINGS, INC.
Reel/Frame 062826/0205 →
SECURITY INTEREST Recorded Dec 16, 2019
From: ROKU, INC.; ROKU DX HOLDINGS, INC.
To: MORGAN STANLEY SENIOR FUNDING, INC.
Reel/Frame 051300/0931 →
CHANGE OF NAME Recorded Nov 20, 2019
From: DATAXU, INC.
To: ROKU DX HOLDINGS, INC.
Reel/Frame 051066/0767 →
RELEASE OF SECURITY INTEREST Recorded Nov 11, 2019
From: SILICON VALLEY BANK, AS ADMINISTRATIVE AGENT
To: DATAXU, INC.
Reel/Frame 050970/0379 →
SECURITY AGREEMENT Recorded Jul 1, 2016
From: DATAXU, INC.
To: SILICON VALLEY BANK, AS ADMINISTRATIVE AGENT
Reel/Frame 039225/0919 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 24, 2011
From: SIMMONS, WILLARD L.; CATANZARO, SANDRO N.
To: DATAXU, INC.
Reel/Frame 027108/0060 →