End cap analytic monitoring method and apparatus

• US 8,502,869 B1
• Filed: 09/03/2008
• Issued: 08/06/2013
• Est. Priority Date: 09/03/2008
• Status: Expired due to Fees

• Current Assignee: Target Brands Inc. (Target Corporation)
• Original Assignee: Target Brands Inc. (Target Corporation)
• Inventors: Fuhr, Jackie Jaclyn, DePape, Neal
• Primary Examiner(s): Ashraf, Waseem
• Application Number:
  US12/203,267
• Time in Patent Office: 1,798 Days
• Field of Search: 348/150
• US Class Current: 348/150
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast

Abstract

Methods and apparatus for monitoring and ranking end caps in a store include video monitoring one or more parameters of end caps, including dwell times, item removal, traffic volume, sales information for each end cap, ranking end caps based on one or more of the monitored parameters to determine for example one or more of end cap efficiency, product desirability, and location desirability.

Claims

1. A system for determining the effectiveness of product locations in a retail store, comprising:

a processor; and

a memory storing instructions that, when executed by the processor, perform an operation comprising;

determining for a first predetermined period of time an average dwell time of customers at a plurality of particular locations within a retail store using a plurality of video cameras directed at the plurality of particular locations, each of the plurality of particular locations having a product for sale;

ranking each of the plurality of particular locations based on a correlation between the average dwell time by customers at the plurality of particular locations and sales information for the product for sale at each of the plurality of particular locations;

monitoring a number of removals of the product for sale at each of the plurality of particular locations;

determining by using facial recognition software for each customer who dwells at at least one of the plurality of particular locations whether the customer is viewing the product for sale at the at least one particular location or is dwelling for a reason unrelated to the product for sale at the at least one particular location;

ignoring each customer dwelling for a reason unrelated to the product for sale at the at least one particular location in determining the average dwell time;

changing the product for sale displayed at each of the plurality of particular locations;

determining for a second predetermined period of time a second average dwell time of customers at a plurality of particular locations within a retail store using the plurality of video cameras directed at the plurality of particular locations;

ranking each of the plurality of particular locations based on a correlation between the second average dwell time by customers at the plurality of particular locations and sales information for the product for sale at each of the plurality of particular locations during the second predetermined period of time;

monitoring during the second predetermined period of time a number of removals of the product for sale at each of the plurality of particular locations;

determining by using facial recognition software for each customer who dwells at at least one of the plurality of particular locations during the second predetermined period of time whether the customer is viewing the product for sale at the at least one particular location or is dwelling for a reason unrelated to the product for sale at the at least one particular location;

ignoring each customer dwelling for a reason unrelated to the product for sale at the at least one particular location in determining the second average dwell time;

comparing sales of the products at the predetermined locations during the first predetermined period of time to the sales of products at the particular locations during the second predetermined period of time to determine the effectiveness of the particular locations on sales of the products;

placing a first product for sale at a first one of said plurality of particular locations for said first predetermined period of time;

placing a second product for sale at said first one of said plurality of plurality of locations for said second predetermined period of time, wherein said first product is a competitive product to said second product; and

comparing sales of said first product with said second product during said first predetermined period of time and during said second predetermined period of time.

2. The system of claim 1, wherein ranking each of the plurality of particular locations further comprises determining a correlation between the average dwell time at each of the plurality of particular locations and a quantity of the product for sale removed from each of the plurality of particular locations.

3. The system of claim 1, and further comprising tracking a volume of customer traffic at each of the plurality of particular locations.

4. The system of claim 1, wherein determining an average dwell time further comprises determining for each of the plurality of particular locations a location average dwell time for each customer of a volume of customer traffic who dwells at the at least one of the plurality of particular locations for at least a certain period of time.

5. The system of claim 4, wherein determining whether the customer is viewing the product for sale at the at least one particular location further comprises identifying whether the customer is facing toward the product for sale at the at least one particular location, and ignoring each customer not facing toward the product for sale in determining the location average dwell time.

6. The system of claim 1, wherein determining the average dwell time of customers at the plurality of particular locations within a store further comprises determining a dwell time for customers at a plurality of end caps of a retail store.

7. A method of determining the effectiveness of an end cap location in a retail store by monitoring video data for a retail store, comprising:

a processor; and

a memory storing instructions that, when executed by the processor, perform an operation comprising;

tracking for a first predetermined period of time with a video camera for each of a plurality of end caps a total number of guests who pass by each of the plurality of end caps, each of said plurality of end caps displaying a product for sale;

tracking for each of the plurality of end caps a first subset of the total number of guests who loiter at each of the plurality of end caps;

determining an average loiter time for each of the plurality of end caps;

ranking the plurality of end caps according to the average loiter time;

monitoring a number of removals of the product for sale at each of the plurality of end caps;

wherein tracking each first subset of the total number of guests who loiter at each of the plurality of end caps further comprises defining a loiter-time subset of each first subset, wherein each loiter-time subset is determined by averaging loiter times of those guests in each first subset who loiter for a period of time exceeding a predetermined loiter time;

determining the effectiveness of the end caps based on said first subset and each loiter-time subset by comparing sales of said product for sale displayed at each end cap;

changing the product for sale displayed at each of the plurality of the end caps;

tracking, for a subsequent second predetermined period of time equal in length to the first predetermined period of time, with a video camera for each of the plurality of end caps a total number of guests who pass by each of the plurality of end caps during the second predetermined period of time;

tracking for each of the plurality of end caps a second subset of the total number of guests who loiter at each of the plurality of end caps during the second predetermined period of time;

determining a second average loiter time for each of the plurality of end caps;

ranking the plurality of end caps according to the second average loiter time;

monitoring a number of removals of the product for sale at each of the plurality of particular locations end caps during the second predetermined period of time;

wherein tracking each second subset of the total number of guests who loiter at each of the plurality of end caps during the second predetermined period of time further comprises defining a second loiter-time subset of each second subset, wherein each second loiter-time subset is determined by averaging loiter times of those guests in each second subset who loiter for a period of time exceeding a predetermined loiter time; and

comparing sales of the products at the end caps during the first predetermined period of time to the sales of products at the end caps during the second predetermined period of time to determine the effectiveness of the location of the end caps on sales of the products;

placing a first product for sale at a first one of said plurality of end caps for said first predetermined period of time;

placing a second product for sale at said first one of said plurality of end caps for said second predetermined period of time, wherein said first product is a competitive product to said second product; and

comparing sales of said first product with said second product during said first predetermined period of time and during said second predetermined period of time.

8. The method of claim 7, wherein determining a first average loiter time further comprises averaging the loiter times for each guest of the first subset.

9. The method of claim 8, wherein determining a first average loiter time further comprises:

ignoring those guests who are loitering at an end cap for a reason unrelated to the product for sale at the end cap;

in determining the first average loiter time.