Forecasting

• US 20080255927A1
• Filed: 04/11/2008
• Published: 10/16/2008
• Est. Priority Date: 04/12/2007
• Status: Abandoned Application

• Current Assignee: Jeffrey Thibeault, Justin Holmes, Peter Sispoidis
• Original Assignee: Jeffrey Thibeault, Justin Holmes, Peter Sispoidis
• Inventors: Thibeault, Jeffrey, Holmes, Justin, Sispoidis, Peter
• Application Number:
  US12/082,445
• Publication Number:
  US 20080255927A1
• Time in Patent Office: Days
• US Class Current: 705/10
• 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: G07F 17/32 for games, toys, sports, or amusements
• CPC Class Codes: G07F 17/3227 Configuring a gaming machine, e.g. downloading personal settings, selecting working parameters

Abstract

A method for forecasting a performance characteristic of a game title is provided and includes selecting base game-play data for the game title, wherein the base-game play data is at least partially responsive to the game-play pattern of a user, generating base sales data for the game title responsive to initial sales data and generating forecast data for the game title responsive to the base sales data and the base game-play data.

Claims

1. A method for forecasting a performance characteristic of a game title, the method comprising:

selecting base game-play data for the game title, wherein the base-game play data is at least partially responsive to the game-play pattern of a user;

generating base sales data for the game title responsive to initial sales data; and

generating forecast data for the game title responsive to the base sales data and the base game-play data.

2. The method of claim 1, wherein said initial sales data includes at least one of said sales forecast data, sales data from previous versions of the game title and sales data from similar game titles.

3. The method of claim 2, wherein generating base sales data includes combining said at least one of said sales forecast data, sales data from previous versions of the game title and sales data from similar game titles.

4. The method of claim 1, wherein generating forecast data includes generating final sales data responsive at least in part to the base sales data.

5. The method of claim 4, wherein generating final sales data includes combining the base sales data with sales modifier data, wherein said sales modifier data includes at least one of seasonal sales modifier data, marketing modifier data, piracy modifier data, pricing modifier data and buzz modifier data.

6. The method of claim 4, further comprising combining the final sales data and the base game-play data to generate life-cycle data.

7. The method of claim 6, further comprising combining the life-cycle data with a life-cycle modifier data to generate the forecast data.

8. The method of claim 7, wherein life-cycle modifier data includes data that relates the number of hours the game is played to the time frame that the game is played.

9. The method of claim 5, wherein sales modifier data includes data that relates the number of units sold to the amount of time the game is played.

10. A system for implementing a method for forecasting the performance of a game title, the system comprising:

a means for selecting base game-play data for the game title, wherein the base-game play data is at least partially responsive to the game-play pattern of a user;

a means for generating base sales data for the game title responsive to initial sales data; and

a means for generating forecast data for the game title responsive to the base sales data and the base game-play data.

11. The system of claim 10, wherein said initial sales data includes at least one of said sales forecast data, sales data from previous versions of the game title and sales data from similar game titles.

12. The system of claim 11, wherein generating base sales data includes combining said at least one of said sales forecast data, sales data from previous versions of the game title and sales data from similar game titles.

13. The system of claim 10, wherein generating forecast data includes generating final sales data responsive at least in part to the base sales data.

14. The system of claim 13, wherein generating final sales data includes combining the base sales data with sales modifier data, wherein said sales modifier data includes at least one of seasonal sales modifier data, marketing modifier data, piracy modifier data, pricing modifier data and buzz modifier data.

15. The system of claim 13, further comprising combining the final sales data and the base game-play data to generate life-cycle data.

16. The system of claim 15, further comprising combining the life-cycle data with a life-cycle modifier data to generate the forecast data.

17. The system of claim 16, wherein life-cycle modifier data includes data that relates the number of hours the game is played to the time frame that the game is played.

18. The method of claim 14, wherein sales modifier data includes data that relates the number of units sold to the amount of time the game is played.

19. A computer readable storage medium having computer executable instructions for implementing a method for forecasting the performance of a game title, the method comprising:

selecting base game-play data for the game title, wherein the base-game play data is at least partially responsive to the game-play pattern of a user;

generating base sales data for the game title responsive to initial sales data; and

generating forecast data for the game title responsive to the base sales data and the base game-play data.

20. The computer readable storage medium of claim 19, wherein generating forecast data includes,

combining the base sales data with sales modifier data to generate final sales data;

processing the final sales data with the base game-play data to generate life-cycle data; and

combining the life-cycle data with life-cycle modifier data to generate the forecast data.