System and method for developing tailored content
View Patent ↗Systems and methods for creating tailored media-content and related offerings based on subscriber-specific data are described. In one embodiment of the present invention, a television content provider, such as a programming or advertising provider, uses subscriber-specific data to create offerings including unique programs or program packages or unique bundles of programs other products and services. The content provider may also use the subscriber-specific data to determine the price a subscriber is willing to pay for specific content or content-related offering.
1. A processor-implemented method for predicting clickstream data, comprising:
determining a point in time of interest;
receiving, at a processor, content information from a content database, the content information describing a content offering at the point in time of interest;
receiving, at the processor, at least one subscriber action for the point in time of interest, the subscriber action comprising at least one command from a subscriber while viewing content;
merging, at the processor, the content information with the subscriber actions to generate an event timeline describing the content information and the subscriber actions over a period of time; and
predicting, based on the event timeline, data that will describe the subscriber's purchasing habits.
2. A method according to claim 1 , further comprising merging the content information received from the content database and the at least one subscriber action to create subscriber choice information.
3. A method according to claim 1 , further comprising assigning a category to the content information and merging the category with the event timeline.
4. A method according to claim 2 , further comprising categorizing the merged content information with the at least one subscriber action for the point in time of interest.
5. A method according to claim 1 , further comprising predicting at least one of:
predicting depression of a volume button on a remote control,
predicting depression of a channel “up” button on the remote control, and
predicting depression of a channel “down” button on the remote control.
6. A method according to claim 1 , further comprising predicting depression of a numeric button on a remote control.
7. A method according to claim 1 , further comprising creating tailored media content that corresponds to the predicted subscriber actions.
8. A method according to claim 7 , wherein the tailored media content comprises content bundled with an advertisement for a product or service.
9. A method according to claim 7 , further comprising distributing the tailored media content to the subscriber.
10. A method according to claim 7 , further comprising tracking popularity of the tailored media content for a period of time.
11. A method according to claim 1 , further comprising creating tailored media content that corresponds to past subscriber actions.
12. A method according to claim 1 , further comprising creating tailored media content that corresponds to a demographic of the subscriber.
13. A method according to claim 1 , further comprising creating tailored media content that corresponds to a purchasing history of the subscriber.
14. A method according to claim 1 , further comprising receiving information related to an alternate video source received by the subscriber.
15. A method according to claim 1 , further comprising presenting types of content available to the subscriber during a period of time, with the types of content comprising an alternate video source.
16. A method according to claim 15 , wherein presenting the types of content available comprises integrating content available from the alternate video source into an electronic programming guide.
17. A method according to claim 1 , further comprising providing the subscriber a log of received content.
18. A method according to claim 1 , further comprising merging the content information and information related to an alternate video source to determine what content is received by the subscriber.
19. A method according to claim 1 , wherein the content information comprises an amount of time that an advertisement was received.
20. A method according to claim 1 , further comprising analyzing the subscriber actions to determine when the subscriber initially receives an entire advertisement but subsequently only receives a portion of the advertisement.
21. A server for predicting subscriber actions, the server operative to:
receive a point in time of interest;
receive content information from a content database, the content information describing a content offering at the point in time of interest;
receive at least one subscriber action from a subscriber-action database, the subscriber action comprising at least one command from a subscriber while viewing the content offering at the point in time of interest;
obtain purchasing data describing the subscriber's historical purchases;
merge the content information, the subscriber actions, and the purchasing data to generate an event timeline describing the subscriber's content selections and the subscriber's purchases over a period of time; and
predict, based on the event timeline, data that will describe the subscriber's purchasing habits at a fixture point in time.
22. The server according to claim 21 , further operative to assign a category to the content information and merge the category with the event timeline.
23. The server according to claim 21 , further operative to predict at least one of depression of a channel button at a remote control and depression of a volume button at the remote control.
24. The server according to claim 21 , further operative to predict depression of a mute button at a remote control.
25. The server according to claim 21 , further operative to predict depression of a “last” channel button at a remote control.
26. A computer readable medium storing processor executable instructions for performing a method, the method comprising:
retrieving content information from a content database, the content information describing a content offering at a point in time of interest;
retrieving subscriber actions from a subscriber-action database, the subscriber actions comprising commands by a subscriber while accessing the content offering at the point in time of interest;
obtaining purchasing data describing the subscriber's purchases;
merging the content information, the subscriber actions, and the purchasing data to generate an event timeline describing the subscriber's content selections and the subscriber's purchases over a period of time; and
predicting, based on the event timeline, future subscriber actions and the subscriber's purchasing habits at a future point in time.
27. A computer program product according to claim 26 , further comprising instructions for assigning a category to the content information and for merging the category with the event timeline.
28. A computer program product according to claim 26 , further comprising instructions for correlating the content information with the subscriber actions.
29. A computer program product according to claim 26 , further comprising instructions for projecting future purchases by the subscriber based on the event timeline.
30. A computer program product according to claim 26 , further comprising instructions for at least one of i) analyzing buttons pushed on a remote control during preceding content and ii) analyzing buttons pushed on the remote control during succeeding content.
31. A computer program product according to claim 26 , further comprising instructions for analyzing buttons pushed by the subscriber to receive an alternate source of content.
32. A computer program product according to claim 26 , further comprising instructions for accessing the subscriber actions taken by the subscriber while accessing and viewing content.
33. A device, comprising:
a processor communicating with memory;
the processor retrieving content information describing a content offering at a point in time of interest;
the processor retrieving subscriber actions comprising commands by a subscriber while receiving the content offering at the point in time of interest;
the processor obtaining purchasing data describing the subscriber's purchases;
the processor merging the content information, the subscriber actions, and the purchasing data to generate an event timeline describing the subscriber's content selections and the subscriber's purchases over a period of time; and
the processor predicting, based on the event timeline, future subscriber actions and future purchases at a future point in time.