System and method for developing tailored content

• US 7,587,323 B2
• Filed: 12/14/2001
• Issued: 09/08/2009
• Est. Priority Date: 12/14/2001
• Status: Expired due to Fees

• Current Assignee: Alphonso, Inc. (LG Corporation)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Swix, Scott R., Matz, William R.
• Primary Examiner(s): OUELLETTE, JONATHAN P
• Application Number:
  US10/017,630
• Publication Number:
  US 20050096920A1
• Time in Patent Office: 2,825 Days
• Field of Search: 705/1
• US Class Current: 705/344
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0207 Discounts or incentives, e.g. coupons or rebates
• CPC Class Codes: G06Q 30/0252 based on events or environment, e.g. weather or festivals
• CPC Class Codes: H04H 60/33 Arrangements for monitoring the users' behaviour or opinions
• CPC Class Codes: H04H 60/43 for identifying broadcast channels
• CPC Class Codes: H04H 60/63 for services of sales data processing systems or methods specially adapted for electronic commerce G06Q30/00
• CPC Class Codes: H04H 60/66 for using the result on distributors' side
• CPC Class Codes: H04N 21/25883 being end-user demographical data, e.g. age, family status or address arrangements for identifying locations of users in broadcast systems H04H60/52
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/266 Channel or content management, e.g. generation and management of keys and entitlement messages in a conditional access system, merging a VOD unicast channel into a multicast channel
• CPC Class Codes: H04N 21/435 Processing of additional data, e.g. decrypting of additional data, reconstructing software from modules extracted from the transport stream
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

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.

Claims

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.