System and methods for tracking consumers in a store environment

• US 20070067220A1
• Filed: 11/20/2006
• Published: 03/22/2007
• Est. Priority Date: 08/29/2000
• Status: Abandoned Application

• Current Assignee: The Procter & Gamble Company
• Original Assignee: The Procter & Gamble Company
• Inventors: Scheid, Mary, Godsey, Ronald, Haine, Marshall
• Application Number:
  US11/602,111
• Publication Number:
  US 20070067220A1
• Time in Patent Office: Days
• US Class Current: 705/23
• CPC Class Codes: G06Q 20/202 Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR
• CPC Class Codes: G06Q 20/203 Inventory monitoring
• CPC Class Codes: G06Q 20/208 Input by product or record sensing, e.g. weighing or scanner processing
• CPC Class Codes: G06Q 30/0237 at kiosk
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G07G 1/0036 Checkout procedures

Abstract

A method of modifying a store environment parameter is provided.

Claims

1. A method of modifying a store environment parameter comprising the steps:

(a) obtaining consumer traffic data of a consumer in a store environment of a store, wherein the store environment comprises the store environment parameter;

(b) obtaining point-of-sale data of the consumer at the store;

(c) analyzing said consumer traffic pattern and said point-of-sale data; and

(d) modifying the store environment parameter within the store based upon said analyzes.

2. The method of claim 1, wherein the step of obtaining the consumer traffic pattern data of the consumer comprises choosing from:

using a radio frequency tag device;

detecting a heat signature of the consumer;

using a video camera; and

combinations thereof.

3. The method of claim 1, wherein the consumer traffic data comprises consumer track data.

4. The method of claim 1, wherein the consumer traffic data comprises consumer traffic data at a particular store location;

wherein the particular store location comprises the store environment parameter, and a product; and

wherein the point-of-sale data comprises data about said product.

5. The method of claim 1, wherein the step of analyzing the consumer traffic pattern data and the point-of-sale data comprises mathematical analysis.

6. The method of claim 5, wherein the step of mathematical analysis comprises statistical analysis.

7. The method of claim 6, wherein the step of statistical analysis comprises regression analysis.

8. The method of claim 6, wherein the step of determining the consumer traffic pattern of the consumer comprises using a radio frequency tag device.

9. The method of claim 1, wherein the store environment comprises multiple store environments.

10. The method of claim 1, wherein the store comprises:

a multiple of stores and multiple store formats.

11. The method of claim 9, wherein the store comprises multiple stores and a multiple store formats.

12. The method of claim 1, wherein the store comprises multiple stores, wherein the consumer traffic pattern data of the consumer and the point-of-sale data of the consumer are transmitted to a single remote data repository.

13. The method of claim 12, wherein the consumer traffic pattern data of the consumer and the point-of-sale data of the consumer is transmitted via the Internet.

14. The method of claim 6, wherein the analysis step comprises using a computer program.

15. The method of claim 1, wherein the real store environmental parameter is chosen from a signage, end cap position, position of special promotion area, position of informational kiosk, type of information kiosk, a store-within-a-store area, shelf configuration, lighting, flooring, scent, aisle length, aisle orientation, aisle configuration, and combinations thereof.

16. The method of claim 1 further comprising the step of conducting an interview with the consumer regarding the environmental parameter.

17. The method of claim 12, wherein the step of analyzing said consumer traffic pattern and said point-of-sale data comprises statistical analysis.

18. The method of claim 17, wherein the wherein the step of obtaining the consumer traffic pattern data of the consumer comprises using a radio frequency tag device.

19. The method of claim 18, wherein the radio frequency tag device is on a product, on a shopping cart, or a combination thereof.

20. The method of claim 17, wherein the point-of-purchase data comprises products purchased.