Apparatus and method for configuring web pages to maximize profits using sales, inventory, and cost data

• US 20030046156A1
• Filed: 08/30/2001
• Published: 03/06/2003
• Est. Priority Date: 08/30/2001
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Cromer, Daryl Carvis, Locker, Howard Jeffrey, Ward, James Peter
• Application Number:
  US09/943,344
• Publication Number:
  US 20030046156A1
• Time in Patent Office: Days
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

A computer-implemented method determines which products are to be advertised as specials on web pages or in another form of advertisement, based on comparing scores generated for each product within a number of products offered for sale to predict the profit potential of the product. Preferably, the score is generated by multiplying a profit factor, indicating a profit for each sale, by a sales factor, determining the likelihood of selling the product, and by an inventory factor, which is included to prevent the advertisement of a product for which an inadequate inventory is held as a special. Preferably, web pages are automatically generated at a predetermined time with products having the best scores being advertised as specials.

Claims

1. A computer-implemented method for generating advertising information offering a plurality of products for sale, comprising a plurality of locations for individual advertisements and including at least one special location for prominently advertising a special product, wherein said method comprises:

providing a first data structure including an entry for each product within said plurality of products, wherein said first data structure includes a field identifying each said product and a field including data relating to profit from sales of each said product;

generating a score for each product within said plurality of products from said data relating to profit from sales;

comparing said score for each product within said plurality of products to determine at least one product with promising profit from sales; and

writing at least one code identifying said at least one product with promising profit from sales to a selection data structure.

2. The computer-implemented method of claim 1, additionally comprising:

reading said at least one code from said selection data structure;

reading product advertising information corresponding to said at least one product from a second data structure including an entry for each product within said plurality of products, an identification field including a code identifying each said product and an information field including information describing each said product; and

writing said product advertising information corresponding to said at least one product to a computer readable medium in at least one location corresponding to said at least one special location for prominently advertising a special product.

3. The computer-implemented method of claim 2, wherein

said computer readable medium includes a computer data structure storing data for presentation as one or more web pages, and

said data for presentation as one or more web pages causes a standard browser to display data in a predetermined manner.

4. The computer-implemented method of claim 1, wherein

said field including data relating to profit from sales of each said product includes a field storing data describing profits from an individual sale of each said product and a field storing sales data describing a level of sales of each said product,

said step of providing said first data structure includes updating said sales data, and

said step of generating a score for each product includes multiplying said data relating to profit from sales of each said product by said sales data for each said product to obtain expected profit data.

5. The computer-implemented method of claim 4, wherein

said first data structure additionally includes a field storing an inventory function derived from inventory data for each said product,

said step of providing said first data structure includes updating said inventory function, and

said step of generating a score for each product includes multiplying said expected profit data by said inventory function to lower said score for a product having a low level of inventory.

6. The computer-implemented method of claim 5, wherein

said sales data and said inventory function are updated in a real-time basis as said products are sold,

aid score is generated and said score for each product is compared iteratively at a predetermined time.

7. The computer-implemented method of claim 5, wherein

said sales data and said inventory function are updated and said score is generated in a real-time basis as said products are sold, and

said score for each product is compared iteratively at a predetermined time.

8. A computer-implemented method for generating advertising information offering a first plurality of products for sale, comprising a first plurality of locations for individual advertisements and including a second plurality of special locations for prominently advertising special products, wherein said method comprises:

providing a first data structure including an entry for each product within said first plurality of products, wherein said first data structure includes a field identifying each said product and a field including data relating to profit from sales of each said product;

generating a score for each product within said first plurality of products from said data relating to profit from sales;

comparing said score for each product to determine a second plurality of products with promising profit from sales, wherein a number of products in said second plurality of products is equal to a number of special locations in said second plurality of special locations; and

writing a code identifying each product within said second plurality of products to an identification data field within a selection data structure.

9. The computer-implemented method of claim 8, additionally comprising:

reading said code identifying each product within said second plurality of products from said selection data structure;

reading product advertising information corresponding to each product within said second plurality of products from a second data structure including an entry for each product within said first plurality of products, an identification field storing a code identifying each said product, and an information field storing information describing each said product; and

writing said product advertising information corresponding to each product within said second plurality of products to a computer readable medium in a second plurality of locations corresponding to said second plurality of special locations for individual advertisements.

10. The computer-implemented method of claim 9, wherein

said computer readable medium includes a computer data structure storing data for presentation as one or more web pages, and

said data for presentation as one or more web pages causes a standard browser to display data in a predetermined manner.

11. The computer-implemented method of claim 10, wherein comparing said score for each product causes products having highest levels of scores to be selected as said second plurality of products.

12. The computer-implemented method of claim 11, wherein

said method additionally comprises initializing data stored within a plurality of score data fields within said selection data structure and writing said score for each product within said second plurality of products to a score data field within said selection data structure associated with a data field storing said code identifying said product,

said score for each product is compared to one or more scores stored within said score data field, and

if said score for each product is larger than one or more scores stored within said score data fields, said data fields within said selection data structure are written to include codes identifying products having highest levels of scores and scores of said products having highest levels of scores.

13. The computer-implemented method of claim 10, wherein

said first data structure additionally includes a field identifying a category among a plurality of categories for each product within said plurality of products,

a number of categories in said plurality of categories is equal to said number of special locations in said second plurality of special locations,

said method additionally comprises initializing data stored within a plurality of score data fields within said selection data structure and writing said score for each product within said second plurality of products to a score data field within said selection data structure associated with an identification data field storing said code identifying said product,

each score data field and each identification data field associated with said score data field within said selection data structure stores data from an entry for which a different category is stored in said first data structure,

said score for each product is compared to a score within a score data field associated with a category stored for said product in said first data structure, and

if said score for each product is larger than said score within said score data field associated with said category, said score for each product is written to said score data field associated with said category.

14. A system for communicating web pages having advertising information offering a plurality of products for sale, comprising a plurality of locations for individual advertisements and including at least one special location for prominently advertising a special product, wherein said system comprises:

a server having an interface for communicating over a switched telephone network;

first data storage including a first data structure and a selection data structure, wherein said first data structure stores an entry for each product within a plurality of products, a field storing data identifying each said product, and a field storing data relating to profit from sales of each said product; and

first processor means programmed to read said data identifying each said product and said data relating to profit from sales of each said product, to generate a score for each said product from said data relating to profit from sales of said product, to compare said scores for each said product to determine at least one product with promising profit from sales, and to write at least one code identifying said at least one product with promising profit from sales to said selection data structure.

15. The system of claim 14, additionally comprising:

second data storage including second and third data structures, wherein said second data structure stores an entry for each product within said plurality of products, an identification field storing data identifying each said product, and an information field including information describing each said product and a third data structure, wherein said third data structure stores data for presentation through said server over said switched telephone network, and wherein said third data structure includes at least one special location corresponding to a prominent display of information presented through said server over said switched telephone network; and

second processor means programmed to read said at least one code and data within said identification and information fields, and to write said product advertising information corresponding to said at least one product to said third data structure in at least one location corresponding to said at least one special location within said third data structure.

16. The system of claim 15, wherein

said field including data relating to profit from sales of each said product includes a field storing data describing profits from an individual sale of each said product and a field storing sales data describing a level of sales of each said product,

said system additionally comprises third processor means updating said sales data, and

said first processor means generates a score for each product by a process including multiplying said data relating to profit from sales of each said product by said sales data for each said product to obtain expected profit data.

17. The system claim 16, wherein

said first data structure additionally includes a field storing an inventory function derived from inventory data for each said product,

said third processor means additionally updates said inventory function, and

said first processor means generates a score for each said product by multiplying said expected profit data by said inventory function to lower said score for a product having a low level of inventory.

18. The computer-implemented method of claim 17, wherein

said third processor means updates said sales data and said inventory function in a real-time basis as said products are sold,

said first processor means generates and compares said score iteratively at a predetermined time.

19. The computer-implemented method of claim 17, wherein

said sales data and said inventory function are updated and said score is generated in a real-time basis as said products are sold, and

said first processor means compares said score for each product iteratively at a predetermined time.

20. A system for communicating web pages having advertising information offering a first plurality of products for sale, comprising a first plurality of locations in for individual advertisements and including a second plurality of special locations for prominently advertising special products, wherein said system comprises:

a server having an interface for communicating over a switched telephone network;

first data storage including a first data structure and a selection data structure, wherein said first data structure stores an entry for each product within said first plurality of products, a field storing data identifying each said product, and a field storing data relating to profit from sales of each said product; and

first processor means programmed to read said data identifying each said product and said data relating to profit from sales of each said product, to generate a score for each said product from said data relating to profit from sales of said product, to compare said scores for each said product to determine a second plurality of products with promising profits from sales, wherein a number of products in said second plurality of products is equal to a number of special locations in said second plurality of special locations, and to write a code identifying each product within said second plurality of products to said selection data structure.

21. The system of claim 20, additionally comprising:

second data storage including second and third data structures, wherein said second data structure stores an entry for each product within said plurality of products, an identification field storing data identifying each said product, and an information field including information describing each said product and a third data structure, wherein said third data structure stores data for presentation through said server over said switched telephone network, and wherein said third data structure includes a second plurality of locations corresponding to said second plurality of special locations for prominently advertising special products; and

second processor means programmed to read said code identifying each product within said second plurality of products and data within said identification and information fields, and to write said product advertising information corresponding to said products in said second plurality of products to said third data structure in said second plurality of locations corresponding to said second plurality of special locations for prominently advertising special products.

22. The system of claim 21, wherein comparing said score for each product causes products having highest levels of scores to be selected as said second plurality of products.

23. The computer-implemented method of claim 22, wherein

said first processor means is additionally programmed to initialize data stored within a plurality of score data fields within said selection data structure and to write said score for each product within said second plurality of products to a score data field within said selection data structure associated with a data field storing said code identifying said product,

said score for each product is compared to one or more scores stored within said score data field, and

if said score for each product is larger than one or more scores stored within said score data fields, said data fields within said selection data structure are written to include codes identifying products having highest levels of scores and scores of said products having highest levels of scores.

24. The computer-implemented method of claim 21, wherein

said first data structure additionally includes a field identifying a category among a plurality of categories for each product within said plurality of products,

a number of categories in said plurality of categories is equal to said number of special locations in said second plurality of special locations,

said first processor means is additionally programmed to initialize data stored within a plurality of score data fields within said selection data structure and to write said score for each product within said second plurality of products to a score data field within said selection data structure associated with an identification data field storing said code identifying said product,

each score data field and each identification data field associated with said score data field within said selection data structure stores data from an entry for which a different category is stored in said first data structure,

said score for each product is compared to a score within a score data field associated with a category stored for said product in said first data structure, and if said score for each product is larger than said score within said score data field associated with said category, said score for each product is written to said score data field associated with said category.

25. The system of claim 21, wherein

said system additionally comprises an inventory control computer accessing sales and inventory data,

said first processing means is provided by a microprocessor within said inventory control computer, and

said second processing means is provided by a microprocessor within said server.

26. The system of claim 21, wherein said first and second processing means are provided by a microprocessor within said server.

27. The system of claim 21, wherein

said system additionally comprises an inventory control computer accessing sales and inventory data and a computing system, and

said first and second processing means are provided by a microprocessor within said computing system.

28. A computer readable medium having computer readable code stored thereon for causing a system including at least one computer to perform a method for generating advertising information offering a first plurality of products for sale, comprising a first plurality of locations for individual advertisements and including a second plurality of special locations for prominently advertising special products, wherein said method comprises:

providing a first data structure including an entry for each product within said first plurality of products, wherein said first data structure includes a field identifying each said product and a field including data relating to profit from sales of each said product;

generating a score for each product within said first plurality of products from said data relating to profit from sales;

comparing said score for each product to determine a second plurality of products with promising profit from sales, wherein a number of products in said second plurality of products is equal to a number of special locations in said second plurality of special locations; and

writing a code identifying each product within said second plurality of products to an identification data field within a selection data structure.

29. The computer readable medium of claim 28, wherein said method additionally comprises:

reading said code identifying each product within said second plurality of products from said selection data structure;

reading product advertising information corresponding to each product within said second plurality of products from a second data structure including an entry for each product within said first plurality of products, an identification field storing a code identifying each said product, and an information field storing information describing each said product; and

writing said product advertising information corresponding to each product within said second plurality of products to a computer data structure in a second plurality of locations corresponding to said second plurality of special locations for individual advertisements.

30. The computer readable medium of claim 29, wherein

said computer data structure stores data for presentation as one or more web pages, and

said data for presentation as one or more web pages causes a standard browser to display data in a predetermined manner.

31. The computer readable medium of claim 30, wherein comparing said score for each product causes products having highest levels of scores to be selected as said second plurality of products.

32. The computer readable medium of claim 31, wherein

said method additionally comprises initializing data stored within a plurality of score data fields within said selection data structure and writing said score for each product within said second plurality of products to a score data field within said selection data structure associated with a data field storing said code identifying said product,

said score for each product is compared to one or more scores stored within said score data field, and

if said score for each product is larger than one or more scores stored within said score data fields, said data fields within said selection data structure are written to include codes identifying products having highest levels of scores and scores of said products having highest levels of scores.

33. The computer readable medium of claim 30, wherein

said first data structure additionally includes a field identifying a category among a plurality of categories for each product within said plurality of products,

a number of categories in said plurality of categories is equal to said number of special locations in said second plurality of special locations,

said method additionally comprises initializing data stored within a plurality of score data fields within said selection data structure and writing said score for each product within said second plurality of products to a score data field within said selection data structure associated with an identification data field storing said code identifying said product,

each score data field and each identification data field associated with said score data field within said selection data structure stores data from an entry for which a different category is stored in said first data structure,

said score for each product is compared to a score within a score data field associated with a category stored for said product in said first data structure, and

if said score for each product is larger than said score within said score data field associated with said category, said score for each product is written to said score data field associated with said category.