Methods and apparatus to deliver targeted advertising
Methods and apparatus to deliver targeted advertising are disclosed. An example apparatus includes a media object assembler to, in response to receiving a request to provide a media object, generate a custom media object using a first media object element and a second media object element based on at least one of a user profile or a group profile corresponding to a user, the user corresponding to the request; an interface to transmit the custom media object to the user; and a performance analyzer to analyze a performance of the custom media object; and update at least one of the user profile or the group profile based on the performance.
1. An apparatus comprising:
a media object assembler to, in response to receiving a request to provide a media object:
generate a first customizable media object element to include in a custom media object, the first customizable media object element based on at least one of a user profile or a group profile corresponding to a user, the user corresponding to the request; and
generate a second customizable media object element independent of the first customizable media object element to include in the custom media object, the second customizable media object element based on at least one of the user profile or the group profile corresponding to the user;
an interface to transmit the custom media object to a computing device of the user via a network communication;
a user profiler to generate the user profile and, when the request corresponds to a new user, generate the user profile; and
a performance analyzer to:
analyze a performance of the custom media object; and
update at least one of the user profile or the group profile using neural network machine learning to adjust ratings of the first customizable media object element and the second customizable media object element based on the performance of the custom media object, the performance analyzer to use the neural network machine learning to adjust the ratings of the first customizable media object element and the second customizable media object element based on a comparison of the performance of the custom media object to previous overlapping custom objects including at least one of the first customizable media object element or the second customizable media object element.
2. The apparatus of claim 1 , wherein the media object assembler is to:
when the request corresponds to the new user, generate the custom media object based on the group profile corresponding to a demographic of the new user; and
when the request corresponds to an old user, generate the custom media object based on the user profile corresponding to the old user.
3. The apparatus of claim 1 , wherein the performance analyzer is to analyze the performance by determining at least one of how the custom media object was presented or how the user interacted with the custom media object.
4. The apparatus of claim 1 , wherein the group profile corresponds to a demographic.
5. The apparatus of claim 1 , wherein the first customizable media object element and the second customizable media object element including at least one of text, audio, video, or an image.
6. A method comprising:
in response to receiving a request to provide a media object, generating, by executing an instruction with a processor, a custom media object using a first media object element and a second media object element independent of the first media object element, the first and second media object elements based on at least one of a user profile or a group profile corresponding to a user, the user corresponding to the request;
transmitting the custom media object to a computing device of the user via the Internet;
generating the user profile when the request corresponds to a new user;
analyzing, by executing an instruction with the processor, a performance of the custom media object; and
updating, by executing an instruction with the processor, at least one of the user profile or the group profile using neural network machine learning to adjust ratings of the first media object element and the second media object element the performance of the custom media object, the neural network machine learning to adjust the ratings of the first media object element and the second media object element based on a comparison of the performance of the custom media object to previous overlapping custom objects including at least one of the first media object element or the second media object element.
7. The method of claim 6 , further including:
when the request corresponds to the new user, generating the custom media object based on the group profile corresponding to a demographic of the new user; and
when the request corresponds to an old user, generating the custom media object based on the user profile corresponding to the old user.
8. The method of claim 6 , wherein the analyzing of the performance includes determining at least one of how the custom media object was presented or how the user interacted with the custom media object.
9. The method of claim 6 , wherein the group profile corresponds to a demographic.
10. The method of claim 6 , wherein the first media object element and the second media object element including at least one of text, audio, video, or an image.
11. A non-transitory computer readable storage medium comprising instructions which, when executed, cause a machine to at least:
in response to receiving a request to provide a media object:
generate a first customizable media object element to include in a custom media object for a user, the first customizable media object element based on at least one of a user profile or a group profile corresponding to the user, the user corresponding to the request; and
generating, by executing an instruction with a processor, the custom media object using a second customizable media object element independent of the first customizable media object element, the first and second customizable media object elements based on at least one of the user profile or the group profile corresponding to the user;
transmit the custom media object to a computing device of the user via a network communication;
generate the user profile when the request corresponds to a new user;
analyze a performance of the custom media object; and
update at least one of the user profile or the group profile using neural network machine learning to adjust ratings of the first customizable media object element and the second customizable media object element based on the performance of the custom media object, the neural network machine learning to adjust the ratings of the first customizable media object element and the second customizable media object element based on a comparison of the performance of the custom media object to previous overlapping custom objects including at least one of the first customizable media object element or the second customizable media object element.
12. The non-transitory computer readable storage medium of claim 11 , wherein the instructions cause the machine to:
when the request corresponds to the new user, generate the custom media object based on the group profile corresponding to a demographic of the new user; and
when the request corresponds to an old user, generate the custom media object based on the user profile corresponding to the old user.
13. The non-transitory computer readable storage medium of claim 11 , wherein the instructions cause the machine to generate the user profile.
14. The non-transitory computer readable storage medium of claim 11 , wherein the instructions cause the machine to analyze the performance by determining at least one of how the custom media object was presented or how the user interacted with the custom media object.
15. The non-transitory computer readable storage medium of claim 11 , wherein the group profile corresponds to a demographic.
16. The non-transitory computer readable storage medium of claim 11 , wherein the first customizable media object element and the second customizable media object element including at least one of text, audio, video, or an image.