AD PLACEMENT
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.
1 . A method comprising:
identifying a plurality of advertisements, each advertisement of the plurality of advertisements having an associated target number of clicks or impressions;
receiving advertisement requests;
determining, using at least one processor, a probability that each advertisement of the plurality of advertisements will be selected if served in connection with a given advertisement request; and
serving the advertisement of the plurality of advertisements with a high probability in response to advertisement requests until a total target number of clicks or impressions is met, the total target number of clicks or impressions being an aggregate of the associated target numbers.
2 . The method as recited in claim 1 , wherein a number of clicks or impressions for a first advertisement of the plurality of advertisements is less than the associated target number of clicks or impressions for the first advertisement.
3 . The method as recited in claim 2 , wherein a number of clicks or impressions for a second advertisement of the plurality of advertisements is greater than the associated target number of clicks or impressions for the second advertisement.
4 . The method as recited in claim 1 , wherein each advertisement of the plurality of advertisements is associated with a single advertiser.
5 . The method as recited in claim 1 , further comprising maintaining a user profile, the user profile including user attributes reflecting interests of a user.
6 . The method as recited in claim 5 , further comprising updating the user attributes of the user profile based on one or more of Internet sites visited by the user, advertisements selected by the user, or internet searching by the user.
7 . The method as recited in claim 5 , further comprising maintaining an advertisement profile for one or more advertisements of the plurality advertisements, each advertisement profile including ad-attributes that reflect how much an advertisement correlates to a given user attribute.
8 . The method as recited in claim 7 , wherein the probability for a particular advertisement is a function of the consumer attributes of a given user and the ad-attributes for the particular advertisement.
9 . The method as recited in claim 1 , wherein serving the advertisement of the plurality of advertisements comprises serving the advertisement to a mobile device.
10 . The method as recited in claim 1 , wherein serving the advertisement of the plurality of advertisements comprises serving the advertisement to a website over the Internet.
11 . A non-transitory computer-readable storage medium including a set of instructions that, when executed, cause at least one processor to perform steps comprising:
identifying a plurality of advertisements, each advertisement of the plurality of advertisements having an associated target number of clicks or impressions;
receiving advertisement requests;
determining a probability that each advertisement of the plurality of advertisements will be selected if served in connection with a given advertisement request; and
serving the advertisement of the plurality of advertisements with the highest probability in response to advertisement requests until a total target number of clicks or impressions is met, the total target number of clicks or impressions being an aggregate of the associated target numbers.
12 . The computer-readable storage medium as recited in claim 11 , wherein a number of clicks or impressions for a first advertisement of the plurality of advertisements is less than the associated target number of clicks or impressions for the first advertisement.
13 . The computer-readable storage medium as recited in claim 12 , wherein a number of clicks or impressions for a second advertisement of the plurality of advertisements is greater than the associated target number of clicks or impressions for the second advertisement.
14 . The computer-readable storage medium as recited in claim 11 , wherein each advertisement of the plurality of advertisements is associated with a single advertiser.
15 . The computer-readable storage medium as recited in claim 11 , further comprising instructions that, when executed, cause at least one processor to maintain a user profile, the user profile including user attributes reflecting interests of a user.
16 . The computer-readable storage medium as recited in claim 15 , further comprising instructions that, when executed, cause at least one processor to update the user attributes of the user profile based on one or more of Internet sites visited by the user, advertisements selected by the user, or internet searching by the user.
17 . The computer-readable storage medium as recited in claim 15 , further comprising instructions that, when executed, cause at least one processor to maintain an advertisement profile for one or more advertisements of the plurality advertisements, each advertisement profile including ad-attributes that reflect how much an advertisement correlates to a given user attribute.
18 . The computer-readable storage medium as recited in claim 17 , wherein the probability for a particular advertisement is a function of the consumer attributes of a given user and the ad-attributes for the particular advertisement.
19 . The computer-readable storage medium as recited in claim 11 , wherein serving the advertisement of the plurality of advertisements comprises serving the advertisement to a mobile device.
20 . The computer-readable storage medium as recited in claim 11 , wherein serving the advertisement of the plurality of advertisements comprises serving the advertisement to a website over the Internet.
21 . A method comprising:
identifying a first advertisement having a first associated target number of clicks or impressions;
identifying a second advertisement having a second associated target number of clicks or impressions;
identifying a plurality of advertisement requests from one or more marketing mediums on one or more mobile devices;
determining, using at least one processor, which of the first advertisement and the second advertisement has a higher probability of selection for advertisement requests of the plurality of advertisement requests; and
serving the first or second advertisement with the higher probability of selection in response to each advertisement request until a total target number of clicks or impressions is met, the total target number of clicks or impressions being an aggregate of the first and second associated target numbers.
22 . The method as recited in claim 21 , wherein a number of clicks or impressions for the first advertisement is less than the first target number of clicks or impressions.
23 . The method as recited in claim 22 , wherein a number of clicks or impressions for the second advertisement is greater than the second associated target number of clicks or impressions.
24 . The method as recited in claim 21 , wherein the first and second advertisements are associated with a single advertiser.
25 . The method as recited in claim 21 , further comprising maintaining a user profile, the user profile including user attributes reflecting interests of a user.
26 . The method as recited in claim 25 , further comprising updating the user attributes of the user profile based on one or more of actions of the user on one or more marketing mediums on one or more mobile devices.
27 . The method as recited in claim 25 , further comprising maintaining an advertisement profile for each of the first and second advertisements, each advertisement profile including ad-attributes that reflect how much the first or second advertisement correlates to a given user attribute.
28 . The method as recited in claim 27 , wherein the probability of selection is a function of the consumer attributes of a given user and the ad-attributes for the first or second advertisement.
29 . The method as recited in claim 21 , wherein one or more marketing mediums comprise a software program.
30 . The method as recited in claim 29 , wherein one or more marketing mediums comprise one or more websites.