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 . (canceled)
2 . A method comprising:
detecting, using at least one processor, an action of a user on a marketing medium;
determining an attribute common to one or more other users who have performed the action on the marketing medium;
selecting, using the at least one processor, one or more advertisements to present to the user based on the attribute common to the one or more other users.
3 . The method as recited in claim 2 , wherein the attribute is a demographic category.
4 . The method as recited in claim 3 , wherein the attribute is gender.
5 . The method as recited in claim 3 , wherein the attribute is geography based.
6 . The method as recited in claim 2 , further comprising serving the one or more advertisements to the user over a communications network.
7 . The method as recited in claim 6 , further comprising serving the one or more advertisements to a website being accessed by the user.
8 . The method as recited in claim 1 , wherein selecting one or more advertisements to present to the user further comprises:
determining a probability that each advertisement of a plurality of advertisements will be selected by the user; and
selecting the advertisement with the highest probability.
9 . The method as recited in claim 2 , wherein selecting one or more advertisements to present to the user based on the attribute common to the one or more other users comprises selecting an advertisement with a high click-thru-rate for users associated with the attribute.
10 . The method as recited in claim 2 , further comprising associating the attribute common to the one or more other users with a user profile for the user.
11 . The method as recited in claim 2 , wherein the marketing medium comprises a software program.
12 . The method as recited in claim 11 , wherein the software program is installed on a mobile device.
13 . The method as recited in claim 12 , wherein the mobile device is a smart device.
14 . The method as recited in claim 11 , wherein the software program comprises an Internet browser.
15 . The method as recited in claim 14 , wherein the action comprises browsing of one or more websites.
16 . A non-transitory computer-readable storage medium including a set of instructions that, when executed, cause at least one processor to perform steps comprising:
detecting an action of a user on a marketing medium;
determining an attribute common to one or more other users who have performed the action on the marketing medium; and
selecting one or more advertisements to present to the user based on the attribute common to the one or more other users.
17 . The computer-readable storage medium as recited in claim 16 , wherein the attribute is a demographic category.
18 . The computer-readable storage medium as recited in claim 17 , wherein the attribute is gender.
19 . The computer-readable storage medium as recited in claim 17 , wherein the attribute is geography based.
20 . The computer-readable storage medium as recited in claim 16 , further comprising instructions that, when executed, cause at least one processor to serve the one or more advertisements to the user over a communications network.
21 . The computer-readable storage medium as recited in claim 20 , further comprising instructions that, when executed, cause at least one processor to serve the one or more advertisements to a website being accessed by the user.
22 . The computer-readable storage medium as recited in claim 16 , further comprising instructions that, when executed, cause at least one processor to:
determine a probability that each advertisement of a plurality of advertisements will be selected by the user; and
select the advertisement with the highest probability.
23 . The computer-readable storage medium as recited in claim 16 , wherein selecting one or more advertisements to present to the user based on the attribute common to the one or more other users comprises selecting an advertisement with a high click-thru-rate for users associated with the attribute.
24 . The computer-readable storage medium as recited in claim 16 , further comprising instructions that, when executed, cause at least one processor to associate the attribute common to the one or more other users with a user profile for the user.
25 . The computer-readable storage medium as recited in claim 16 , wherein the marketing medium comprises a software program.
26 . The computer-readable storage medium as recited in claim 25 , wherein the software program is installed on a mobile device.
27 . The computer-readable storage medium as recited in claim 26 , wherein the mobile device is a smart device.
28 . The computer-readable storage medium as recited in claim 25 , wherein the software program comprises an Internet browser.
29 . The computer-readable storage medium as recited in claim 28 , wherein the action comprises browsing of one or more websites.
30 . A method comprising:
associating an interest category with a user based at least in part on an action of the user on a marketing medium;
determining an attribute common to one or more other users associated with the interest category;
selecting, using the at least one processor, one or more advertisements to present to the user based on the attribute common to the one or more other users; and
serving the one or more advertisements to the user over a communications network.
31 . The method as recited in claim 30 , wherein the attribute is a demographic category.
32 . The method as recited in claim 31 , wherein the attribute is gender.
33 . The method as recited in claim 31 , wherein the attribute is geography based.
34 . The method as recited in claim 30 , wherein the communications network comprises the Internet.
35 . The method as recited in claim 34 , further comprising serving the one or more advertisements to a website being accessed by the user.
36 . The method as recited in claim 35 , wherein selecting one or more advertisements to present to the user based on the attribute common to the one or more other users comprises selecting an advertisement with a high click-thru-rate for users associated with the attribute.
37 . The method as recited in claim 31 , wherein the interest category comprises one of sports, business, finance, health, or gardening.
38 . The method as recited in claim 31 , wherein selecting one or more advertisements to present to the user further comprises:
determining a probability that one or more advertisements of a plurality of advertisements will be selected by the user; and
selecting the advertisement with the highest probability.
39 . The method as recited in claim 30 , further comprising associating the attribute common to the one or more other users with a user profile for the user.
40 . The method as recited in claim 30 , wherein the marketing medium comprises a software program.
41 . The method as recited in claim 40 , wherein the software program is installed on a mobile device.
42 . The method as recited in claim 41 , wherein the mobile device is a smart device.
43 . The method as recited in claim 40 , wherein the software program comprises an Internet browser.
44 . A non-transitory computer-readable storage medium including a set of instructions that, when executed, cause at least one processor to perform steps comprising:
associating an interest category with a user based at least in part on an action of the user on a marketing medium;
determining an attribute common to one or more other users associated with the interest category;
selecting one or more advertisements to present to the user based on the attribute common to the one or more other users; and
serving the one or more advertisements to the user over a communications network.
45 . The computer-readable storage medium as recited in claim 44 , wherein the attribute is a demographic category.
46 . The computer-readable storage medium as recited in claim 44 , wherein the attribute is gender.
47 . The computer-readable storage medium as recited in claim 45 , wherein the attribute is geography based.
48 . The computer-readable storage medium as recited in claim 44 , wherein the communications network comprises the Internet.
49 . The computer-readable storage medium as recited in claim 48 , further comprising instructions that, when executed, cause at least one processor to serve the one or more advertisements to a website being accessed by the user.
50 . The computer-readable storage medium as recited in claim 49 , wherein selecting one or more advertisements to present to the user based on the attribute common to the one or more other users comprises selecting an advertisement with a high click-thru-rate for users associated with the attribute.
51 . The computer-readable storage medium as recited in claim 44 , wherein the interest category comprises one of sports, business, finance, health, or gardening.
52 . The computer-readable storage medium as recited in claim 44 , further comprising instructions that, when executed, cause at least one processor to:
determine a probability that one or more advertisements of a plurality of advertisements will be selected by the user; and
select the advertisement with the highest probability.
53 . The computer-readable storage medium as recited in claim 44 , further comprising instructions that, when executed, cause at least one processor to associate the attribute common to the one or more other users with a user profile for the user.
54 . The computer-readable storage medium as recited in claim 44 , wherein the marketing medium comprises a software program.
55 . The computer-readable storage medium as recited in claim 54 , wherein the software program is installed on a mobile device.
56 . The computer-readable storage medium as recited in claim 55 , wherein the mobile device is a smart device.
57 . The computer-readable storage medium as recited in claim 54 , wherein the software program comprises an Internet browser.
58 . A method comprising:
associating an interest category with a user based at least in part on an action of the user on a marketing medium installed on a mobile device;
determining an attribute common to one or more other users associated with the interest category;
selecting, one or more advertisements to present to the user based on the attribute common to the one or more other users; and
serving the one or more advertisements to the mobile device.
59 . The method as recited in claim 58 , wherein the attribute is a demographic category.
60 . The method as recited in claim 59 , wherein the attribute is gender.
61 . The method as recited in claim 59 , wherein the attribute is geography based.
62 . The method as recited in claim 58 , further comprising serving the one or more advertisements to a website being accessed by the user on the mobile device.
63 . The method as recited in claim 58 , wherein selecting one or more advertisements to present to the user based on the attribute common to the one or more other users comprises selecting an advertisement with a high click-thru-rate for users associated with the attribute.
64 . The method as recited in claim 58 , wherein the interest category comprises one of sports, business, finance, health, or gardening.
65 . The method as recited in claim 58 , wherein selecting one or more advertisements to present to the user further comprises:
determining a probability that one or more advertisements of a plurality of advertisements will be selected by the user; and
selecting the advertisement with the highest probability.
66 . The method as recited in claim 58 , further comprising associating the attribute common to the one or more other users with a user profile for the user.
67 . The method as recited in claim 58 , wherein the marketing medium comprises a software program.
68 . The method as recited in claim 67 , wherein the software program comprises an Internet browser.
69 . The method as recited in claim 58 , wherein the mobile device is a smart device.