Customer management system

• US 20020143609A1
• Filed: 01/18/2002
• Published: 10/03/2002
• Est. Priority Date: 01/19/2001
• Status: Abandoned Application

• Current Assignee: RPX Corporation
• Original Assignee: RPX Corporation
• Inventors: Magouirk, Brent, Wallace, Shawn E., Kennan, William B.
• Application Number:
  US10/052,577
• Publication Number:
  US 20020143609A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/06311 Scheduling, planning or task assignment for a person or group
• CPC Class Codes: G06Q 10/063116 Schedule adjustment for a person or group
• CPC Class Codes: G06Q 10/0875 Itemisation or classification of parts, supplies or services, e.g. bill of materials
• CPC Class Codes: G06Q 10/1097 Task assignment
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A computer-implemented method of updating an electronic schedule is provided. The method includes a step of statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers. The method also includes a step of developing at least one recommended action item to be taken with respect to a current potential buyer based on results of the statistical analysis. Finally, the method includes the step of automatically updating an electronic schedule with at least one task representing the at least one recommended action item.

Claims

1. A computer-implemented method of updating an electronic schedule, comprising:

statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers;

developing at least one recommended action item to be taken with respect to a current potential buyer based on results of the statistical analysis; and

automatically updating an electronic schedule with at least one task representing the at least one recommended action item.

2. The computer-implemented method of claim 1, further comprising the steps of:

developing more than one recommended action item; and

automatically updating the electronic schedule with more than one task, wherein the electronic schedule is updated with a task that corresponds to each of the recommended action items.

3. The computer-implemented method of claim 1, wherein statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers further comprises:

statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers that include at least one purchaser and at least one non-purchaser.

4. The computer-implemented method of claim 1, wherein developing at least one recommended action item to be taken with respect to a current potential buyer based on results of the statistical analysis further comprises:

developing at least one recommended action item to be taken with respect to a current potential buyer based on at least one rule that is applied to the collection of data representing historical interactions with the plurality of previous potential buyers.

5. The computer-implemented method of claim 1, wherein developing at least one recommended action item to be taken with respect to a current potential buyer based on results of the statistical analysis further comprises:

developing at least one recommended action item to be taken with respect to a specific current potential buyer based on a determination that the collection of data representing historical interactions with the plurality of previous potential buyers shows that the specific potential buyer has not been contacted for a predetermined about of time.

6. The computer-implemented method of claim 1, wherein statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers further comprises:

determining at least one pattern demonstrated by a group of the plurality of previous potential buyers.

7. The computer-implemented method of claim 6, wherein determining at least one pattern demonstrated by a group of the plurality of previous potential buyers further comprises:

determining at least one trend based on environmental data characteristics.

8. The computer-implemented method of claim 7, wherein determining at least one trend based on environmental data characteristics further comprises:

determining at least one trend based on an environmental data characteristic selected from the group consisting of product type, product cost, potential buyer'"'"'s target cost, potential buyer'"'"'s gender, potential buyer'"'"'s age, salesperson'"'"'s gender, the weather, and salesperson'"'"'s age.

9. The computer-implemented method of claim 1, further comprising automatically rescheduling the task if it is not performed as scheduled.

10. The computer-implemented method of claim 1, further comprising automatically re-assigning the task if is not performed as scheduled.

11. The computer-implemented method of claim 1, wherein determining the recommended action item includes selecting an appropriate task type.

12. The computer-implemented method of claim 11, wherein determining the recommended action item includes selecting an appropriate task type selected from the group consisting of sending flowers, sending an email, contacting by telephone, sending a gift, sending a newsletter and sending a gift certificate.

13. The computer-implemented method of claim 1, wherein determining the recommended action item includes selecting a timing and frequency for the at least one task.

14. The computer-implemented method of claim 1, wherein statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers further comprises:

statistically analyzing a collection of data representing historical interactions between a single sales entity and a plurality of previous potential buyers.

15. The computer-implemented method of claim 1, wherein statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers further comprises:

statistically analyzing a collection of data representing historical interactions between a plurality of sales entities and a plurality of previous potential buyers.

16. The computer-implemented method of claim 1, wherein statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers further comprises

statistically analyzing a collection of data that has been stripped of client confidential information and represents historical interactions between a plurality of sales entities and a plurality of previous potential buyers.

18. The computer-implemented method of claim 17, wherein performing a task that corresponds to the at least one recommended action item further comprises:

performing the task in response to a user directive.

19. The computer-implemented method of claim 17, wherein performing a task that corresponds to the at least one recommended action item further comprises:

automatically performing the task.

17. A computer-implemented method of assigning and performing tasks based on statistical analysis, comprising:

statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers;

developing at least one recommended action item to be taken with respect to a current potential buyer based on results of the statistical analysis; and

performing a task that corresponds to the at least one recommended action item.

20. A system for assigning and performing tasks based on statistical analysis, comprising:

means for statistically analyzing a collection of data representing historical interactions with a plurality of previous potential buyers;

means for developing at least one recommended action item to be taken with respect to a current potential buyer based on results of the statistical analysis; and

means for performing a task that corresponds to the at least one recommended action item.