IP Library Granted Patent US 10,586,191
Granted Patent B2
US 10,586,191 · App. 14/883,263 · Granted Mar 10, 2020

Arranging a store in accordance with data analytics

Inventors: George Dimitrios Fanourgiakis (Foster City, CA); Manolis Dimitrios Fanourgiakis (Foster City, CA); Dylan Tatz (San Francisco, CA); Leo Smirnov (San Francisco, CA)
Assignee: TECHNI, LLC
G06Q10/06313G06Q10/0637G06Q30/0201G06Q30/0242G06Q30/0246
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Quick Facts
Patent No.
US 10,586,191
App. No.
14/883,263
Granted
Mar 10, 2020
Kind
B2
Abstract

A system can access data about items for a store and generate a plan for configuring the store based on the accessed data. The system can further provide, for example, information for configuring reconfigurable shelving units so as to produce the layout of the store according to the plan.

Claims (25)

1. A computer system comprising:

one or more processors; and

a non-transitory computer-readable storage medium having stored therein instructions that, when executed by the one or more processors of the computer system, cause the computer system to at least:

access data associated with one or more items for a store, the store comprising a reconfigurable shelving unit, the reconfigurable shelving unit comprising a plurality of components that are configured for re-arranging relative to one another between different configurations so as to change a footprint of the reconfigurable shelving unit by at least one of changing a length of the shelving unit or changing a curvature of the shelving unit;

generate a plan for configuring the store in a layout based at least in part upon the data, the plan including information for configuring or reconfiguring the reconfigurable shelving unit by at least one of changing the length of the shelving unit or changing the curvature of the shelving unit or moving the shelving unit to a new location within the store; and

cause one or more devices to interact with the plurality of components to move, configure, or reconfigure the reconfigurable shelving unit in accordance with the plan.

2. The computer system of claim 1 , wherein the data comprises data about the one or more items that is based at least in part on data about a set of people comprising at least one of customers of the store or persons identified as prospective customers of the store.

3. The computer system of claim 1 , wherein the data comprises at least one of data about a fixture of the store or a product of the store.

4. The computer system of claim 1 , wherein the data comprises at least one of data about a purchasing history of the one or more items in the store, data about a purchasing history of the one or more items at locations other than the store, data about a demand for the one or more items, data about a popularity of the one or more items, data about a profitability of the one or more items, data about revenue streams for the one or more items, or data about a characteristic of the one or more items.

5. The computer system of claim 1 , wherein the data comprises data acquired within the store.

6. The computer system of claim 5 , wherein the data comprises at least one of data acquired through cameras positioned within the store, data acquired by sensors on shelving units positioned within the store, data acquired by proximity sensors positioned within the store, data acquired by weight sensors positioned within the store, data acquired by seismic sensors positioned within the store, data acquired by wireless sensors positioned within the store, or data acquired by RFID (radio-frequency identification) sensors positioned within the store.

7. The computer system of claim 5 , wherein the data comprises at least one of data about foot traffic, data about loiter time, data about a location of a product in the store, data about a position of a fixture in the store, or data about a heart rate of a customer in the store.

8. The computer system of claim 1 , wherein the data comprises data acquired remote from the store.

9. The computer system of claim 8 , wherein the data comprises at least one of tax data, housing data, locale trend data, sports data, event data, government holiday data, religious holiday data, data about ages living in an area, medical data, income data, stock market data, credit card data, police data, fire data, crime data, disaster data, birthday data, weather data, environmental data, U.S. Census data, demographic data, locale design data, trending data, school data, real estate data, traffic data, social media data, food trends data, or product trends data.

10. A computer system comprising:

one or more processors; and

a non-transitory computer-readable storage medium having stored therein instructions that, when executed by the one or more processors of the computer system, cause the computer system to at least:

access data associated with a set of people comprising at least one of customers of a store or persons identified as prospective customers of the store, the store comprising a reconfigurable shelving unit, the reconfigurable shelving unit comprising a plurality of components that are configured for re-arranging relative to one another between different configurations so as to change a footprint of the reconfigurable shelving unit by at least one of changing a length of the shelving unit or changing a curvature of the shelving unit;

generate a plan for configuring the store in a layout based at least in part upon the data, the plan including information for configuring or reconfiguring the reconfigurable shelving unit by at least one of changing the length of the shelving unit or changing the curvature of the shelving unit or moving the shelving unit to a new location within the store; and

cause one or more devices to interact with the plurality of components to move, configure, or reconfigure the reconfigurable shelving unit in accordance with the plan.

11. The computer system of claim 10 , wherein the data comprises data acquired about people within the store.

12. The computer system of claim 11 , wherein the data comprises at least one of data acquired through cameras positioned within the store, data acquired by sensors on shelving units positioned within the store, data acquired by proximity sensors positioned within the store, data acquired by weight sensors positioned within the store, data acquired by seismic sensors positioned within the store, data acquired by wireless sensors positioned within the store, or data acquired by RFID (radio-frequency identification) sensors positioned within the store.

13. The computer system of claim 11 , wherein the data comprises at least one of data about foot traffic, data about loiter time, or data about a heart rate of a customer in the store.

14. The computer system of claim 10 , wherein the data comprises data acquired remote from the store.

15. The computer system of claim 14 , wherein the data comprises at least one of tax data, housing data, locale trend data, sports data, event data, government holiday data, religious holiday data, data about ages living in an area, medical data, income data, stock market data, credit card data, police data, fire data, crime data, disaster data, birthday data, weather data, environmental data, census data, U.S. Census data, demographic data, locale design data, trending data, school data, real estate data, traffic data, social media data, food trends data, or product trends data.

Assignments (2)
CORRECTIVE ASSIGNMENT TO CORRECT THE ADDING ADDITIONAL PROPERTIES LISTED ON THE ASSIGNMENT PREVIOUSLY RECORDED AT REEL: 050210 FRAME: 0212. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Aug 30, 2019
From: STOREXPERTS INC
To: TECHNI, LLC
Reel/Frame 050238/0298 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 13, 2016
From: FANOURGIAKIS, GEORGE DIMITRIOS; FANOURGIAKIS, MANOLIS DIMITRIOS; TATZ, DYLAN; SMIRNOV, LEO
To: STOREXPERTS, INC.
Reel/Frame 037478/0844 →
Continuity (2)
Provisional Application 62063903 · Oct 14, 2014
Related Publication 20160104175A1 · Apr 14, 2016