Scheduling delivery of products via the internet

• US 20010047285A1
• Filed: 03/16/2001
• Published: 11/29/2001
• Est. Priority Date: 05/10/2000
• Status: Active Grant

• Current Assignee: JUNE RAY LIMITED
• Original Assignee: Webvan Group, Inc.
• Inventors: Nijhawan, Sandeep, Bhargava, Sunil, Wijaya, Joyo, Borders, Louis H.
• Granted Patent: US 7,139,721 B2
• Time in Patent Office: Days
• US Class Current: 705/8
• CPC Class Codes: G06Q 10/06314 Calendaring for a resource
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

Methods and apparatus for scheduling delivery of an order via a wide area network. A computer system associates a customer point value with each customer according to a customer point system. The customer point values is determined with reference to customer order data. The computer system then divides the customers into customer groups, each of which has a range of customer point values. The system determines an actual capacity allocation distribution among the customer groups based on the customer order data. The system adjusts the range of customer point values for customer groups to cause the actual capacity allocation distribution to converge to a target capacity allocation distribution.

Claims

1. A method for allocating system capacity among a plurality of customers in a system, comprising:

associating a customer point value with each customer according to a customer point system, the customer point values being determined with reference to customer order data;

dividing the plurality of customers into a plurality of customer groups, each customer group corresponding to a range of customer point values, each customer being assigned to one of the plurality of customer groups according to the associated customer point value;

determining an actual capacity allocation distribution among the plurality of customer groups with reference to the customer order data; and

adjusting the range of customer point values associated with selected customer groups to cause the actual capacity allocation distribution to converge to a target capacity allocation distribution.

2. The method of

claim 1

wherein the plurality of customer groups includes a new customer group corresponding to those of the plurality of customers associated with the system less than a predetermined period of time.

3. The method of

claim 2

wherein the new customer group is determined without reference to the customer point system.

4. The method of

claim 1

further comprising allocating system capacity among the plurality of customers according to the customer groups.

5. The method of

claim 4

wherein the system capacity comprises delivery resources capacity.

6. The method of

claim 5

wherein allocating system capacity comprises generating a delivery window grid for presentation to a specific customer, the availability of specific windows in the delivery window grid being determined with reference to the customer group to which the specific customer is assigned.

7. The method of

claim 4

further comprising associating customer group overrides with selected ones of the plurality of customers, allocating system capacity for the selected being done with reference to the customer group overrides.

8. The method of

claim 1

wherein the customer order data for each customer comprise at least one of customer order size and customer order frequency.

9. The method of

claim 1

further comprising iterating division of the plurality of customers into the customer groups, determination of an actual capacity allocation distribution, and adjustment of the customer point value ranges to effect convergence of the actual capacity allocation distribution to the target capacity allocation distribution.

10. The method of

claim 1

wherein the method is entirely automated.

11. The method of

claim 1

wherein at least a portion of the method is performed manually.

12. The method of

claim 11

wherein the portion of the method performed manually is adjusting the customer point value ranges.

13. A computer implemented method for generating a delivery interface in which a plurality of delivery windows are presented on a remote platform via a wide area network, the method comprising:

determining which of the plurality of delivery windows are available for delivery of an order with reference to currently available system resources and a customer profile;

generating the delivery interface; and

transmitting the delivery interface to the remote platform via the wide area network.

14. The method of

claim 13

, wherein the customer profile corresponds to one of a plurality of groups, each group representing customer activities.

15. The method of

claim 14

, wherein a level of customer activities is characterized by an average shipment size associated with the customer profile.

16. The method of

claim 15

, wherein the level of customer activities is characterized by a shipment frequency associated with the customer profile.

17. The method of

claim 16

, wherein the customer profile includes an override group name;

and wherein determining is performed based on which of the corresponding group name, and the corresponding override group name is dominant.

18. The method of

claim 17

, wherein the override group name is associated with an override expiration date after which determining is performed based on the corresponding group name.

19. The method of

claim 18

, wherein the set of groups includes a group for a new customer which is determined based on a difference between an earliest purchase time of the customer, and a time of determining.

20. The method of

claim 19

, wherein the delivery interface indicates information based on the group name of the customer.