System and method for calculating store display layouts

• US 8,983,865 B1
• Filed: 09/21/2012
• Issued: 03/17/2015
• Est. Priority Date: 09/21/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Murphy, Bruce W.
• Primary Examiner(s): Danneman, Paul
• Application Number:
  US13/624,796
• Time in Patent Office: 907 Days
• Field of Search: None
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 10/101 Collaborative creation, e.g. joint development of products or services
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A system and machine-implemented method for associating a product category of consumer products with a location is provided. Data corresponding to consumer products is received, using one or more computing devices. Data for each of the consumer products includes corresponding location information. Each of the consumer products is identified based on the received data, using the one or more computing devices. A product category for each of the identified consumer products is determined, using the one or more computing devices. The consumer products are grouped based on the determined product categories and the corresponding location information, using the one or more computing devices. At least one determined product category is associated and stored with at least one location based on a density of the grouped consumer products and the corresponding location information, using the one or more computing devices.

Claims

1. A computer-implemented method of associating a product category of consumer products with a location, the method comprising:

receiving, using one or more computing devices, data corresponding to consumer products, wherein the data is received from one or more mobile devices and the data for each of the consumer products includes location data of a mobile device from the one or more mobile devices at a time the mobile device captured the data corresponding to the consumer product;

identifying, using the one or more computing devices, each of the consumer products based on the received data;

determining, using the one or more computing devices, a product category for each of the identified consumer products;

grouping, using the one or more computing devices, the consumer products based on the product categories determined for the consumer products and the corresponding location data for the consumer products;

associating and storing, using the one or more computing devices, at least one determined product category with at least one location based on a density of the grouped consumer products and the corresponding location data; and

creating, using the one or more computing devices, a layout corresponding to a physical layout of an area of interest based on the association of the at least one determined product category with the at least one location, the layout providing a representation of the at least one product category at the at least one location.

2. The computer-implemented method of claim 1, wherein the received data corresponding to consumer products are images of the consumer products.

3. The computer-implemented method of claim 2, wherein identifying each of the consumer products based on the received data comprises comparing characteristics of the images of the consumer products with known characteristics of consumer products stored in the data repository.

4. The computer-implemented method of claim 3, wherein the characteristics of the images of the consumer products include at least one of text, a shape, a color, or a pattern.

5. The computer-implemented method of claim 2, wherein the images of the consumer products contain at least one of bar codes or quick response (QR) codes attached to the consumer products.

6. The computer-implemented method of claim 5, wherein the at least one of bar codes or QR codes attached to the consumer products are identified based on the graphical patterns of the bar codes or QR codes.

7. The computer-implemented method of claim 1, wherein the received data corresponding to consumer products are descriptions of the consumer products entered as spoken natural language or text inputs.

8. The computer-implemented method of claim 1, further comprising receiving, using the one or more computing devices, additional data corresponding to additional consumer products, wherein the layout corresponding to the physical layout of the area of interest is updated based on the received additional data.

9. A machine-readable medium comprising instructions stored therein, which when executed by a processor, cause the processor to perform operations comprising:

receiving one or more images containing consumer products, each of the one or more images including corresponding location data, wherein the one or more images are received from one or more mobile devices, and wherein the location corresponding to each of the one or more images is location of a mobile device from the one or more mobile devices at a time of capturing the image;

identifying the consumer products based on the received images;

determining a product category for each of the identified consumer products;

grouping the customer products based on the product categories determined for the customer products and the corresponding location data for the customer products; and

associating and storing at least one determined product category with at least one location based on a density of the grouped customer products and the corresponding location data;

creating a layout corresponding to a physical layout of an area of interest based on the association of the at least one determined product category with the corresponding location data, the layout providing a representation of the at least one product category at the at least one location.

10. The machine-readable medium of claim 9, wherein the location of each mobile device from the one or more mobile devices is determined based on at least one of global positioning service coordinates of the mobile device, a location of a Wi-Fi network to which the mobile device is connected, or a cellular triangulation of the mobile device.

11. The machine-readable medium of claim 9, wherein grouping the images based on the determined product categories and the corresponding location data creates clusters of product categories, wherein a cluster of a product category is identified as a group of consumer products for a given area with a density higher than a predetermined threshold, and each cluster having a corresponding location.

12. The machine-readable medium of claim 11, wherein the instructions for creating the layout corresponding to the physical layout of the area of interest includes instructions to create the layout based on the clusters of product categories and the corresponding locations, the layout providing a representation of product categories at different locations of the layout.

13. The machine-readable medium of claim 12, further comprising instructions for receiving additional data corresponding to additional consumer products, wherein the layout corresponding to the physical layout of the area of interest is updated based on the received additional data.

14. The machine-readable medium of claim 13, wherein each of the clusters comprises an associated confidence level based on the density of the group of consumer products for the given area, and wherein the layout corresponding to the physical layout of the area of interest is updated when the received additional data corresponding to the additional consumer produces causes the associated confidence level to fall below a predetermined threshold.

15. A system for associating a product category of consumer products with a location, the system comprising:

one or more processors; and

a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising;

receiving data corresponding to consumer products, wherein data for each of the consumer products includes corresponding location data;

identifying each of the consumer products based on the received data;

determining a product category for each of the identified consumer products;

grouping the consumer products based on the product categories determined for the consumer products and the corresponding location data for the consumer products into clusters, wherein each cluster comprises a product category and a given location; and

creating a layout corresponding to a physical layout of an area of interest based on the clusters, the layout providing a representation of the product categories at different locations of the layout.

16. The system of claim 15, wherein the consumer products are grouped into clusters when the consumer products have a density higher than a predetermined threshold for a given area.

17. The system of claim 15, wherein the machine-readable medium further comprises instructions for receiving additional data corresponding to additional consumer products, wherein the layout corresponding to the physical layout of the area of interest is updated based on the received additional data.