Discrete choice method of reporting and predicting multiple transaction types

• US 20060104213A1
• Filed: 11/18/2004
• Published: 05/18/2006
• Est. Priority Date: 11/18/2004
• Status: Active Grant

• Current Assignee: Alvaria Cayman
• Original Assignee: Rockwell Electronics Commerce Technologies LLC
• Inventors: Sumner, Roger, Dezonno, Anthony
• Granted Patent: US 8,184,547 B2
• Time in Patent Office: Days
• US Class Current: 370/252
• CPC Class Codes: H04L 41/00 Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/34 Signalling channels for network management communication

Abstract

The method for and system or apparatus for forecasting future communication transaction traffic from a customer include the steps of or structure for: collecting communication channel data on at least first and second communication channels; performing a numeric transformation to the data; calculating a discrete choice probability for each communication channel; and forecasting future period usage values for a user on a communication channel.

Claims

1. A method for forecasting future communication transaction traffic from a customer comprising the steps of:

a) collecting communication channel data on at least first and second communication channels;

b) performing a numeric transformation to the data;

c) calculating a discrete choice probability for each communication channel; and

d) forecasting future period usage values for a user on a communication channel.

2. The method of claim 1 wherein the first communication channel is selected from one of a voice telephone number, a data telephone number, an email address, a sip address, an uniform resource locator (URL) address, an URI address, an Internet Protocol (IP) address, an instant messaging identifier, and a cable box identifier.

3. The method of claim 1 wherein the second communication channel is selected from one of a voice telephone number, a data telephone number, an email address, a sip address, an uniform resource locator (URL) address, an URI address, an Internet Protocol (IP) address, a instant messaging identifier, and a cable box identifier.

4. The method of claim 1 wherein the numeric transformation uses at least one of an exponential formula, a Hayes transformation, or a logit function.

5. The method of claim 1 wherein the calculation of a discrete choice probability results from an arithmetic operation of the numeric transforms.

6. The method of claim 1 wherein the calculation of a discrete choice probability results from a logical operation of the numeric transforms.

7. The method of claim 1 wherein the forecasting of future values uses a least mean squares formula.

8. The method of claim 1 wherein the forecast is displayed on one of a printout from a printer or a visual display.

9. The method of claim 1, wherein the discrete choice probability of a communications channel is pA|[A,B], and

pA|[A,B]=UA/(UA+UB)

where UA is exponential transform value of a first communication channel value;

where UB is is the exponential transform value of a second communication channel value; and

where (UA+UB) is sum of the numeric transforms of multiple channels.

10. The method of claim 1, wherein the discrete choice probability of a communications channel equals 1, and

pA+pB=1

where pA is the probability of use of a first communication channel value;

and

where pB is the probability of use of a second communication channel value.

11. A computer-readable media tangibly embodying a program of instructions executable by a computer to perform a method of forecasting transaction usage levels, the method comprising the steps of:

a) collecting communication channel data on at least two communication channels;

b) performing a numeric transformation to the data;

c) calculating a discrete choice probability for each communication channel; and

d) forecasting future period values for a communication channel being used.

12. The computer-readable media of claim 11 wherein said media comprise at least one of a RAM, a ROM, a disk, an ASIC, a PROM.

13. A computer-readable media tangibly embodying a program of instructions executable by a computer to perform a method of forecasting transaction usage levels, the method comprising:

collecting communication channel data on at least two communication channels;

performing a numeric transformation to the data;

calculating a discrete choice probability for each communication channel; and

forecasting future period usage values for a user on a communication channel.

14. The computer-readable media of claim 13 wherein said media comprise at least one of a RAM, a ROM, a disk, an ASIC, a PROM.

15. An apparatus for forecasting future communication transaction traffic from a customer comprising:

means for collecting communication channel data on at least two communication channels;

means for performing a numeric transformation to the data;

means for calculating a discrete choice probability for each communication channel; and

means for forecasting future period usage values for a user on a communication channel.

16. An apparatus for forecasting future communication transaction traffic from a customer comprising:

means for collecting communication channel data on at least two communication channels;

means for performing a numeric transformation to the data;

means for calculating a discrete choice probability for each communication channel; and

means for forecasting future period usage values for a communication channel.

17. An apparatus programmed to forecast future communication transaction traffic comprising:

a communications interface to a transaction processing system, wherein said communication interface provides communication traffic level information about a communications channel to a computing system; and

a processing system, said processing system being disposed within the computing system for forecasting future period usage values for at least one communication channel.

18. An apparatus programmed to forecast future communication transaction traffic comprising:

a communications interface to a transaction processing system, wherein said communication interface provides communication traffic level information about a user of a communications channel to a computing system; and

a processing system, said processing system being disposed within the computing system for forecasting future period usage values for a user of at least one communication channel.

19. A computer programmed to execute a process of forecasting communication transaction traffic, the process comprising:

collecting communication channel data on at least two communication channels;

performing a numeric transformation to the data; and

calculating a discrete choice probability for each communication channel.

20. The computer of claim 19, wherein the process further comprises:

forecasting future period usage values for a user of a communication channel.

21. The computer of claim 19, wherein the process further comprises:

forecasting period usage values for a communication channel.

22. The process of forecasting communication transaction traffic of claim 19 wherein the collecting of communication channel data further comprises defining the communication channel as being a telephone number of an automatic contact distributor and the data as being call traffic level of the telephone number of the automatic contact distributor.

23. The process of claim 19, wherein the discrete choice probability of a communications channel is pA|[A,B], and

pA|[A,B]=UA/(UA+UB)

where UA is exponential transform value of a first communication channel value;

where UB is the exponential transform value of a second communication channel value; and

where (UA+UB) is sum of the numeric transforms of multiple channels.

24. The process of claim 19, wherein the probability choosing communications channel equals 1, and

pA+pB=1

where pA is the probability of use of a first communication channel value;

and

where pB is the probability of use of a second communication channel value.

25. A method for forecasting future communication transaction traffic from a customer including the steps of:

collecting over a selected time period N versions of communication data including at least two communication transaction types, the first type of communication transactions being identified as Type A and the second type of communication transactions being identified as Type B;

tabulating the data collected;

performing a numeric transformation to the data;

calculating a discrete choice probability for each communication type;

forecasting future period values for the types of transactions being used; and

displaying the forecast.

26. The method of claim 25 wherein the Type A transaction type uses one of a voice telephone number, a data telephone number, an email address, a sip address, an uniform resource locator (URL) address, an URI address, an Internet Protocol (IP) address, a instant messaging identifier, or a cable box identifier

27. The method of claim 25 wherein the Type B transaction type uses one of a voice telephone number, a data telephone number, an email address, a sip address, an uniform resource locator (URL) address, an URI address, an Internet Protocol (IP) address, a instant messaging identifier, or a cable box identifier.

28. The method of claim 25 wherein the numeric transformation uses discrete choice modeling.

29. The method of claim 25 wherein the numeric transformation uses an exponential formula.

30. The method of claim 25 wherein the numeric transformation uses Hayes modeling.

31. A system for forecasting future communication transaction traffic from a customer comprising:

hardware and software for collecting over a selected time period N versions of communication data including at least two communication transaction types, the first type of communication transactions being identified as Type A and the second type of communication transactions being identified as Type B;

hardware and software for tabulating the data collected;

hardware and software for performing a numeric transformation to the data;

hardware and software for calculating a discrete choice probability for each communication type;

hardware and software for forecasting future period values for the types of transactions being used; and

display structure for displaying the forecast.

32. The system of claim 31 wherein the Type A transaction type uses one of a voice telephone number, a data telephone number, an email address, a sip address, an uniform resource locator (URL) address, an URI address, an Internet Protocol (IP) address, a instant messaging identifier, or a cable box identifier.

33. The method of claim 31 wherein the Type B transaction type uses one of a voice telephone number, a data telephone number, an email address, a sip address, an uniform resource locator (URL) address, an URI address, an Internet Protocol (IP) address, a instant messaging identifier, or a cable box identifier.

34. The system of claim 31 wherein the numeric transformation uses discrete choice modeling.

35. The system of claim 31 wherein the numeric transformation uses an exponential formula.

36. The system of claim 31 wherein the numeric transformation uses Hayes modeling.