METHOD AND SYSTEM FOR INTEGRATING SPATIAL ANALYSIS AND DATA MINING ANALYSIS TO ASCERTAIN FAVORABLE POSITIONING OF PRODUCTS IN A RETAIL ENVIRONMENT

• US 20030055707A1
• Filed: 09/22/1999
• Published: 03/20/2003
• Est. Priority Date: 09/22/1999
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: BUSCHE, FREDERICK D., MARCOTTE, DAVID
• Application Number:
  US09/400,583
• Publication Number:
  US 20030055707A1
• 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 30/0268 at point-of-sale [POS]
• CPC Class Codes: G06Q 30/0281 Customer communication at a business location, e.g. providing product or service information, consulting
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

A method and system for ascertaining the favorable positioning of products in a retail environment is provided. The locations of products within a retail space are determined using a position identifying system, such as a global positioning system, a local positioning system, or an enhanced global positioning system as products are stocked within the retail space. The paths of customers through the retail space are also determined using the position identifying system, and these paths may be sensed and recorded using a device that stores a position identifier broadcast by the position identifying system. Customers may be identified using financial transaction databases or other identifying data. The products chosen for purchase by the customers are identified, and the locations of the chosen products within the retail space are associated with the paths of the customers through the retail space to form a set of spatial relationships. Data mining algorithms are used to generate input data for forming a set of spatial relationships. Spatial analysis techniques are used to formulate the set of spatial relationships.

Claims

1. A method for determining data relationships of data associated with product placement in a retail space, the method comprising the computer-implemented steps of:

determining locations of products within the retail space using a position identifying system;

identifying customers within the retail space;

recording paths of customers through the retail space using the position identifying system;

identifying products chosen for purchase by the customers during the paths of the customers through the retail space; and

associating the locations of products within the retail space with the paths of the customers through the retail space to form a set of spatial relationships.

2. The method of claim 1 further comprising:

employing data mining algorithms to generate input data for forming the set of spatial relationships.

3. The method of claim 1 further comprising:

employing spatial analysis algorithms to form the set of spatial relationships.

4. The method of claim 1 wherein the position identifying system comprises a global positioning system or other remote sensing device.

5. The method of claim 1 wherein the position identifying system comprises a local positioning system that may or may not be associated with a global positioning system.

6. A method for determining data relationships of data associated with product placement in a retail space, the method comprising the computer-implemented steps of:

identifying patterns of customers in the retail space;

identifying locations of products within the retail space; and

associating the patterns of customers with the locations of products to form a set of spatial relationships.

7. The method of claim 6 further comprising:

selecting locations for products in the retail space based on the set of spatial relationships.

8. The method of claim 7 further comprising:

identifying locations of products relocated within the retail space based on the selected locations; and

associating the patterns of customers with the locations of relocated products to form a second set of spatial relationships.

9. The method of claim 6 further comprising:

employing data mining algorithms to generate input data for forming the set of spatial relationships.

10. The method of claim 6 further comprising:

employing spatial analysis algorithms to form the set of spatial relationships.

11. The method of claim 6 further comprising:

identifying patterns of customers and locations of products within the retail space comprises using a position identifying system.

12. The method of claim 11 wherein the position identifying system comprises a local positioning system that may or may not be associated with a global positioning system.

13. The method of claim 11 wherein the position identifying system comprises a global positioning system or some other means of sensing position of objects of interest.

14. A method for determining data relationships of data associated with product placement, the method comprising the computer-implemented steps of:

identifying patterns of persons within a physical space;

identifying locations of products within a physical space; and

associating the patterns of persons with the locations of products to form a set of spatial relationships.

15. The method of claim 14 wherein the physical space is a warehouse of products.

16. A data processing system for determining data relationships of data associated with product placement in a retail space, the data processing system comprising:

determining means for determining locations of products within the retail space using a position identifying system;

first identifying means for identifying customers within the retail space;

recording means for recording paths of customers through the retail space using the position identifying system;

second identifying means for identifying products chosen for purchase by the customers during the paths of the customers through the retail space; and

associating means for associating the locations of products within the retail space with the paths of the customers through the retail space to form a set of spatial relationships.

17. The data processing system of claim 16 further comprising:

first employing means for employing data mining algorithms to generate input data for forming the set of spatial relationships.

18. The data processing system of claim 16 further comprising:

second employing means for employing spatial analysis algorithms to form the set of spatial relationships.

19. The data processing system of claim 16 wherein the position identifying system comprises a global positioning system.

20. The data processing system of claim 16 wherein the position identifying system comprises a local positioning system.

21. A data processing system for determining data relationships of data associated with product placement in a retail space, the data processing system comprising:

first identifying means for identifying patterns of customers in the retail space;

second identifying means for identifying locations of products within the retail space; and

first associating means for associating the patterns of customers with the locations of products to form a set of spatial relationships.

22. The data processing system of claim 21 further comprising:

selecting means for selecting locations for products in the retail space based on the set of spatial relationships.

23. The data processing system of claim 22 further comprising:

third identifying means for identifying locations of products relocated within the retail space based on the selected locations; and

second associating means for associating the patterns of customers with the locations of relocated products to form a second set of spatial relationships.

24. The data processing system of claim 21 further comprising:

first employing means for employing data mining algorithms to generate input data for forming the set of spatial relationships.

25. The data processing system of claim 21 further comprising:

second employing means for employing spatial analysis algorithms to form the set of spatial relationships.

26. The data processing system of claim 21 further comprising:

fourth identifying means for identifying patterns of customers and locations of products within the retail space comprises using a position identifying system.

27. The data processing system of claim 26 wherein the position identifying system comprises a local positioning system.

28. The data processing system of claim 26 wherein the position identifying system comprises a global positioning system.

29. A data processing system for determining data relationships of data associated with product placement, the data processing system comprising:

first identifying means for identifying patterns of persons within a physical space;

second identifying means for identifying locations of products within a physical space; and

associating means for associating the patterns of persons with the locations of products to form a set of spatial relationships.

30. The data processing system of claim 29 wherein the physical space is a warehouse of products.