Digital content subscription conditioning system

• US 20020169700A1
• Filed: 08/27/2001
• Published: 11/14/2002
• Est. Priority Date: 05/11/2001
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services GmbH (Accenture PLC)
• Inventors: Connie Ko, Dinghw A., Minh Tsai, Ta Chih, Huffman, Lon Joseph
• Granted Patent: US 7,505,936 B2
• Time in Patent Office: Days
• US Class Current: 705/35
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/12 Accounting
• CPC Class Codes: H04M 15/00 Arrangements for metering, time-control or time indication ; Metering, charging or billing arrangements for voice wireline or wireless communications, e.g. VoIP
• CPC Class Codes: H04M 15/44 Augmented, consolidated or itemized billing statement or bill presentation
• CPC Class Codes: H04M 2215/0104 Augmented, consolidated or itemised billing statement, e.g. additional billing information, bill presentation, layout, format, e-mail, fax, printout, itemised bill per service or per account, cumulative billing, consolidated billing

Abstract

Allocating subscription revenue may involve receiving usage information relating to usage of digital content (e.g., music, movies, text, images, games) in a digital content aggregation, identifying a coefficient relating to a subset of digital works in the digital content aggregation (e.g., author-specific subjective or objective factors, popularity ranking, historical factors, performance factors, etc.), and generating a revenue allocation for the digital content based on the coefficient and the usage information.

Claims

1. A computer-implemented method of allocating digital content subscription revenue, the method comprising:

receiving usage information relating to usage of digital content in a digital content aggregation;

identifying a coefficient relating to a subset of digital works in the digital content aggregation; and

generating a revenue allocation for the digital content based on the coefficient and the usage information.

2. The method of claim 1, wherein the coefficient is derived from a measure of usage for digital content calculated using usage information from a plurality of digital service providers.

3. The method of claim 1, wherein the coefficient comprises a preset value corresponding to a subjective measure of marketability for the digital content.

4. The method of claim 3, wherein the coefficient corresponds to an author of digital content.

5. The method of claim 4, wherein identifying the coefficient comprises retrieving the coefficient from a contract data repository.

6. The method of claim 1, wherein identifying the coefficient comprises identifying a plurality of conditioning coefficients, each comprising a preset value.

7. The method of claim 6, wherein the conditioning coefficients correspond to an author of digital content.

8. The method of claim 7, wherein one or more of the preset values indicates that a particular conditioning coefficient does not apply and is not to be used in generating the revenue allocation.

9. The method of claim 8, wherein identifying the conditioning coefficients comprises retrieving the conditioning coefficients from a central data repository to enable continuous updates to revenue allocation models.

10. The method of claim 7, wherein generating the revenue allocation comprises:

averaging the preset values for each of a plurality of digital works in the digital content aggregation to create a composite conditioning coefficient for each of the digital works; and

multiplying the composite conditioning coefficient by the usage information.

11. The method of claim 10, wherein generating the revenue allocation further comprises normalizing data during multiplication to create a royalty percentage of subscription revenue for each digital work used in a given period.

12. The method of claim 10, wherein generating the revenue allocation further comprises assigning a weight to each conditioning coefficient before the averaging.

13. The method of claim 10, wherein the conditioning coefficients comprise at least one of the following:

number of top ten songs for an artist;

number of platinum records for the artist;

number of years the artist has been with a label;

number of records produced by the artist; and

a popularity ranking for the artist.

14. The method of claim 1, further comprising receiving digital asset metadata from a digital asset management system to facilitate assigning of digital content aggregations and the generating of the revenue allocation.

16. The data processing system of claim 15, wherein the input/output system comprises a network interface, a serial port and a keyboard.

17. The data processing system of claim 16, wherein the database comprises a submission database, a subscription agreement and conditioning coefficient database, and a server database.

18. The data processing system of claim 17, further comprising a network server configured to present a graphical user interface for receiving submissions and managing the subscription agreement and conditioning coefficient database.

19. The data processing system of claim 17, wherein the revenue conditioning server comprises data exchange software capable of translating output data into a destination-specific format.

20. The data processing system of claim 19, wherein the revenue conditioning server comprises a back-end server having document routing, mapping and transformation, transaction logging, subscriber management, security certification, and workflow orchestration elements.

15. A data processing system for allocating digital content subscription revenue, the system comprising:

a processor;

an input/output system;

a database; and

a revenue conditioning server configured to calculate revenue allocations for digital content in an aggregation of digital content by allocating earned revenue for the aggregation as a whole based upon actual usage of the digital content and a conditioning coefficient.

21. A data processing system for allocating digital content subscription revenue, the system comprising:

means for processing data;

means for storing data on a storage medium;

means for initializing the storage medium;

first means for receiving digital content usage data;

second means for receiving one or more conditioning coefficients relating to author-specific valuations of digital content;

third means for receiving earned subscription revenue data;

means for calculating revenue allocations per digital asset, wherein the revenue allocations vary with amount of usage of each digital asset in a given time period, and wherein the revenue allocations vary with the one or more conditioning coefficients; and

means for transmitting the revenue allocations per digital asset.

22. The data processing system of claim 21, wherein the means for calculating comprises a software component of a revenue conditioning server.

23. The data processing system of claim 22, wherein the means for storing comprises a relational database.

24. The data processing system of claim 23, wherein the first, second and third means for receiving comprise software modules in a computer network interface program.

25. The data processing system of claim 24, wherein the revenue conditioning server comprises data exchange software capable of translating output data into a destination-specific format.

26. The data processing system of claim 25, wherein the revenue conditioning server comprises a back-end server having document routing, mapping and transformation, transaction logging, subscriber management, security certification, and workflow orchestration elements.

27. The data processing system of claim 21, further comprising:

means for receiving digital asset metadata; and

means for transmitting cost data for digital assets to a digital server provider, wherein the cost data includes cost information per asset.

29. The machine-readable medium of claim 28, wherein the coefficient is derived from a measure of usage for digital content calculated using usage information from a plurality of digital service providers.

30. The machine-readable medium of claim 28, wherein the coefficient corresponds to an author of digital content.

31. The machine-readable medium of claim 30, wherein the coefficient comprises a preset value corresponding to a subjective measure of marketability for the digital content.

32. The machine-readable medium of claim 31, wherein identifying the coefficient comprises retrieving the coefficient from a contract data repository.

33. The machine-readable medium of claim 30, wherein identifying the coefficient comprises identifying a plurality of conditioning coefficients, each comprising a preset value.

34. The machine-readable medium of claim 33, wherein at least one of the preset values indicates that a particular conditioning coefficient does not apply and is not to be used in generating the revenue allocation.

35. The machine-readable medium of claim 34, wherein generating the revenue allocation comprises:

averaging the preset values for each of a plurality of digital works in the digital content aggregation to create a composite conditioning coefficient for each of the plurality of digital works; and

multiplying the composite conditioning coefficient by the usage information.

36. The machine-readable medium of claim 35, wherein generating the revenue allocation further comprises normalizing data in multiplication to create a royalty percentage of subscription revenue for each digital work used in a given period.

37. The machine-readable medium of claim 35, wherein generating the revenue allocation further comprises assigning a weight to each conditioning coefficient before the averaging.

38. The machine-readable medium of claim 35, wherein the conditioning coefficients comprise at least one of the following:

number of top ten songs for an artist;

number of platinum records for the artist;

number of years the artist has been with a label;

number of records produced by the artist; and

a popularity ranking for the artist.

39. The machine-readable medium of claim 33, wherein identifying the plurality of conditioning coefficients comprises retrieving the conditioning coefficients from a central data repository.

28. A machine-readable medium having stored thereon one or more sequences of instructions for causing one or more machines to perform operations comprising:

receiving usage information relating to usage of digital content in a digital content aggregation;

identifying a coefficient relating to a subset of digital works in the digital content aggregation; and

generating a revenue allocation for the digital content based on the coefficient and the usage information.