Method and system for quantifying relative immediacy of events and likelihood of occurrence

• US 20060224435A1
• Filed: 04/01/2005
• Published: 10/05/2006
• Est. Priority Date: 04/01/2005
• Status: Abandoned Application

• Current Assignee: David Taylor, Kenneth F. Male
• Original Assignee: David Taylor, Kenneth F. Male
• Inventors: Taylor, David, Male, Kenneth F.
• Application Number:
  US11/096,351
• Publication Number:
  US 20060224435A1
• 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: G06Q 30/0203 Market surveys; Market polls

Abstract

A method and system for quantifying market research. In one embodiment, a method of quantifying a likelihood of a plurality of events occurring within a specified time frame includes receiving a plurality of qualitative data corresponding to each one of the plurality of events. The method also includes quantifying the qualitative data to obtain a plurality of quantitative data corresponding to each one of the plurality of events. The method also includes processing the quantitative data to determine a respective likelihood of the plurality of events occurring within a specified time. The method still further includes generating a report that standardizes the respective likelihood of the plurality of events occurring within the specified time frame.

Claims

1. A method of quantifying the respective likelihood of a plurality of events occurring within a specified time frame, said method comprising:

a) receiving a plurality of qualitative data respectively corresponding to each one of said plurality of events;

b) quantifying each one of the qualitative data respectively corresponding to each one of said plurality of events to obtain a plurality of quantitative data respectively corresponding to each one of said plurality of events;

c) processing said plurality of quantitative data to determine the respective likelihood of said plurality of events occurring within said specified time frame; and

d) generating a report that standardizes the respective likelihood of said plurality of events occurring within said specified time frame.

2. A method according to claim 1, wherein each one of said plurality of events comprises the adoption of a particular technology.

3. The method of claim 1, wherein said step of receiving a plurality of qualitative data comprises querying a plurality of users for their need for the technologies.

4. The method of claim 3, wherein said step of receiving a plurality of qualitative data comprises querying users on their intentions to acquire the technologies.

5. The method of claim 3, wherein said step of receiving a plurality of qualitative data comprises querying users on the probability of their acquiring the technologies.

6. The method of claim 3, wherein said step of receiving a plurality of qualitative data comprises querying users on the immediacy of their need for the technology.

7. The method of claim 3, wherein said step of receiving a plurality of qualitative data comprises determining, for each one of said plurality of users, whether a user has the funding to acquire the technology.

8. The method of claim 3, wherein said step of receiving a plurality of qualitative data comprises querying users on their spending on products related to the technology.

9. The method of claim 8, wherein said step of receiving a plurality of qualitative data comprises prompting querying users to select one of a plurality of different time periods for their spending on products related to the technology and said step of quantifying each one of said qualitative data comprises assigning a numeric value to each one of said plurality of different time periods.

10. The method of claim 8, wherein said step of processing said plurality of quantitative data comprises determining spending weights according to spending quartile.

11. The method of claim 8, wherein said step of processing said plurality of quantitative data comprises assigning a time frame weight to each one of the plurality of different time periods and calculating a time frame score for each one of the plurality of different time periods based on the percentage of usage responses, the time frame weight and the spending weights for said respective time period.

12. The method of claim 8, wherein said step of processing said plurality of quantitative data comprises summing the time frame scores to obtain a raw heat index for each technology and scaling the scores to lie between a range of numeric values.

13. A computer readable medium storing program code which, when executed, causes a computer to perform a method of quantifying the respective likelihood of a plurality of events occurring within a specified time frame, the method comprising:

a) receiving a plurality of qualitative data respectively corresponding to each one of said plurality of events;

b) quantifying each one of the qualitative data respectively corresponding to each one of said plurality of events to obtain a plurality of quantitative data respectively corresponding to each one of said plurality of events;

c) processing said plurality of quantitative data to determine the respective likelihood of said plurality of events occurring within said specified time frame; and

d) generating a report that standardizes the respective likelihood of said plurality of events occurring within said specified time frame.

14. The computer readable medium storing program code according to claim 13, wherein each one of said plurality of events comprises the adoption of a particular technology.

15. The computer readable medium storing program code according to claim 13, wherein said step of receiving a plurality of qualitative data comprises querying a plurality of users for their need for the technologies.

16. The computer readable medium storing program code according to claim 15, wherein said step of receiving a plurality of qualitative data comprises querying users on their intentions to acquire the technologies.

17. The computer readable medium storing program code according to claim 15, wherein said step of receiving a plurality of qualitative data comprises querying users on the probability of their acquiring the technologies.

18. The computer readable medium storing program code according to claim 15, wherein said step of receiving a plurality of qualitative data comprises querying users on the immediacy of their need for the technology.

19. The computer readable medium storing program code according to claim 15, wherein said step of receiving a plurality of qualitative data comprises determining, for each one of said plurality of users, whether the user has the funding to acquire the technology.

20. The computer readable medium storing program code according to claim 15., wherein said step of receiving a plurality of qualitative data comprises querying users on their spending on products related to the technology.

21. The computer readable medium storing program code according to claim 20, wherein said step of receiving a plurality of qualitative data comprises prompting querying users to select one of a plurality of different time periods for their spending on products related to the technology and said step of quantifying each one of said qualitative data comprises assigning a numeric value to each one of said plurality of different time periods.

22. The computer readable medium storing program code according to claim 20, wherein said step of processing said plurality of quantitative data comprises determining spending weights according to spending quartile.

23. The computer readable medium storing program code according to claim 20, wherein said step of processing said plurality of quantitative data comprises assigning a time frame weight to each one of the plurality of different time periods and calculating a time frame score for each one of the plurality of different time periods based on the percentage of usage responses, the time frame weight and the spending weights for said respective time period.

24. The computer readable medium storing program code according to claim 20, wherein said step of processing said plurality of quantitative data comprises summing the time frame scores to obtain a raw heat index for each technology and scaling the scores to lie between a range of numeric values.