Ad placement

Patent metadata

Field	Value
Publication number	US-10217129-B2
Application number	US-201213705056-A
Country	US
Kind code	B2
Filing date	Dec 4, 2012
Priority date	Nov 8, 1999
Publication date	Feb 26, 2019
Grant date	Feb 26, 2019

Abstract

This invention concerns optimal ad selection for Web pages by selecting and updating an attribute set, obtaining and updating an ad-attribute profile, and optimally choosing the next ad. The present invention associates a set of attributes with each customer. The attributes reflect the customers' interests and they incorporate the characteristics that impact ad selection. Similarly, the present invention associates with each ad an ad-attribute profile in order to calculate a customer's estimated ad selection probability and measure the uncertainty in that estimate. An ad selection algorithm optimally selects which ad to show based on the click probability estimates and the uncertainties regarding these estimates.

First claim

The invention claimed is:

1. A method comprising:
receiving, by at least one server, one or more advertisements associated with a campaign, the campaign having an associated number of impressions or clicks;
determining, by the at least one server, a first probability that the one or more advertisements will be selected by a plurality of users sharing a demographic when the one or more advertisements are served to client devices associated with the plurality of users via a first network-based media type;
determining, by the at least one server, a second probability that the one or more advertisements will be selected by the plurality of users sharing the demographic when the one or more advertisements are served to the client devices associated with the plurality of users via a second network-based media type, wherein the first network-based media type and the second network-based media type comprise a diverse set of network-based media types;
allocating, by at least one server, a number of impressions or clicks of the associated number of impressions or clicks of the one or more advertisements for serving to client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type as a function of the first probability and the second probability as follows:
Max Σ i,j p ij ζ ij V i , wherein:
Σ j ζ ij ≤1 for all i;
Σ i p ij ζ ij V i ≤(1+δ)G j for all j, where δ controls the smoothness of the campaign;
ζ ij ≥0 for all i and j, and wherein:
V i is the expected impressions per period of media type i;
p ij is the probability of a click on media type i for campaign j;
G j is the total target number of clicks for campaign j for the period;
ζ ij is the percent of all impressions from media type i allocated to campaign j; and
wherein allocating the number of impressions or clicks optimizes placement of the one or more advertisements across the diverse set of network-based media types based on the first probability and the second probability; and

serving, by at least one server and over a network, the one or more advertisements to the client devices associated with the plurality of users via both the first network-based media type and the second network-based media type according to the allocated number of impressions or clicks for each of the first network-based media type and the second network-based media type.

2. The method as recited in claim 1 , further comprising allocating a minimum number of impressions or clicks to serve to the client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type.

3. The method as recited in claim 2 , further comprising allocating a maximum pre-set tolerance number of impressions or clicks to serve to the client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type.

4. The method as recited in claim 1 , further comprising allocating the number of impressions or clicks to serve to the client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type as a function of an expected number of impressions or clicks during a period of time for each of the first network-based media type and the second network-based media type.

5. The method as recited in claim 4 , further comprising allocating the number of impressions clicks to serve to the client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type as a function of a target number of impressions or clicks for the campaign.

6. The method as recited in claim 5 , further comprising allocating the number of impressions or clicks to serve to the client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type as a function of a percent of all impressions or clicks from each of the first network-based media type and the second network-based media type to be allocated to the campaign.

7. The method as recited in claim 1 , wherein the first probability and the second probability are each a function of observed click-thru-rates; and
the method further comprising adjusting the first probability for an advertisement based on an uncertainty level of the observed click-thru-rates, wherein the uncertainty level is inversely proportional to a number of times the advertisement has been previously served.

8. The method as recited in claim 1 , further comprising:
determining a third probability that the one or more advertisements will be selected when served via a third network-based media type;
allocating another number of impressions or clicks of the associated number of impressions or clicks to serve to the client devices associated with the plurality of users via the third network-based media type as a function of the third probability; and
serving the one or more advertisements to the client devices associated with the plurality of users via the third network-based media type according to the another allocated number of impressions or clicks.

9. The method as recited in claim 1 , wherein:
the first network-based media type comprises websites; and
the second network-based media type comprises mobile devices.

10. A non-transitory computer-readable storage medium including a set of instructions that, when executed, cause at least one processor to perform steps comprising:
receiving one or more advertisements associated with a campaign, the campaign having an associated number of impressions or clicks;
determining a first probability that the one or more advertisements will be selected by a plurality of users sharing a demographic when the one or more advertisements are served to client devices associated with the plurality of users via a first network-based media type;
determining a second probability that the one or more advertisements will be selected by the plurality of users sharing the demographic when the one or more advertisements are served to the client devices associated with the plurality of users via a second network-based media type, wherein the first network-based media type and the second network-based media comprise a diverse set of network-based media types;
allocating a number of impressions or clicks of the associated number of impressions or clicks of the one or more advertisements for serving to the client devices associated with the plurality of users via each of the first network-based media type and the second network-based media type as a function of the first probability and the second probability as follows:
Max Σ i,j p ij ζ ij V i , wherein:
Σ j ζ ij ≤1 for all i;
Σ i p ij ζ ij V i ≤(1+δ)G j for all j, where δ controls the smoothness of the campaign;
ζ ij ≥0 for all i and j, and wherein:
V i is the expected impressions per period of media type i;
p ij is the probability of a click on media type i for campaign j;
G j is the total target number of clicks for campaign j for the period;
ζ ij is the percent of all impressions from media type i allocated to campaign j; and
wherein allocating the number of impressions or clicks optimizes placement of the one or more advertisements across the diverse set of network-based media types based on the first probability and the second probability; and

serving the one or more advertisements to the client devices associated with the plurality of users via both the first network-based media type and the second network-based media type according to the allocated number of impressions or clicks for each of th

Assignees

• Facebook Inc

Inventors

• Ferber John B
• Ferber Scott
• Kretsinger Stein E
• Luenberger Robert
• Luenberger David

Classifications

• G06Q30/0244

  Optimization · CPC title

• G06Q30/0254 Primary

  based on statistics · CPC title

• G06Q30/0246 Primary

  Traffic · CPC title

• G06Q30/0241

  Advertisements · CPC title

• G06Q30/0277

  Online advertisement · CPC title