Systems and methods for product placement optimization by sensing customer traffic in stores

1. An in-store customer traffic analysis system, comprising:

a sensor network comprising a plurality of biometric sensors positioned within a retail store, the plurality of biometric sensors comprising a first sensor;

a plurality of displays comprising a first display;

one or more memory devices storing instructions; and

one or more hardware processors configured to execute the instructions to:

receive, from the sensor network over an electronic communications network, a first sensor signal indicating that a first user has been recognized by the first sensor;

determine, based on a first user identifier within the first sensor signal, a first user demographic category associated with the first user;

obtain demographic-display data associated with the first user demographic category;

determine a recommendation to be displayed in the first display based on the demographic-display data;

generate a processor-executable instruction to modify directional signage of the first display towards a product in the retail store according to the recommendation;

determine, based on sensor data from the sensor network, a direction from which the first user approached the first display and an amount of time the first user spent within a proximity of the first display, wherein the direction is determined using a directional sensor within the sensor network;

calculate a first score based on the amount of time the first user spent within the proximity of the first display and the direction from which the first user approached the first display;

associate the first score with the first user demographic category;

generate, based on the first score, a display-demographic map indicating a correlation between the first display and the first user demographic category; and

store the display-demographic map.

2. The system of claim 1 , wherein the one or more hardware processors are further configured to execute the instructions to generate a first foot traffic record associated with the first user based on the first sensor signal.

3. The system of claim 1 , wherein the first sensor senses at least one of a face of the first user, a fingerprint of the first user, or a voice of the first user.

4. The system of claim 1 , wherein the one or more hardware processors are further configured to execute instructions to:

obtain a first user profile corresponding to the first user; and

identify the first user demographic category based on the first user profile.

5. The system of claim 4 , wherein the one or more hardware processors are further configured to execute instructions to:

obtain an inventory listing associated with the retail store; and

generate the recommendation for the product contained in the inventory listing, based on the display-demographic map.

6. The system of claim 5 , wherein the one or more hardware processors are further configured to execute instructions to:

provide the recommendation for the product contained in the inventory listing via a graphical user interface.

7. The system of claim 6 , wherein the one or more hardware processors are further configured to execute instructions to:

obtain a user input via the graphical user interface in response to providing the recommendation for the product contained in the inventory listing;

generate a display instruction based on the user input; and

provide the display instruction via the graphical user interface.

8. The system of claim 1 , wherein the one or more hardware processors are further configured to execute instructions to: update, based on the amount of time the first user spent within the proximity of the first display, a second score indicating an interest of members of a second user demographic group associated with the first user in the first display in a time slot of a particular day.

9. The system of claim 1 , wherein the one or more hardware processors are further configured to execute instructions to:

receive a second sensor signal indicating that a second user has been recognized by the first sensor;

extract a second user identifier from the second sensor signal;

correlate the second sensor signal to the first display;

generate a second foot traffic record associated with the second user identifier and the first display, based on the second sensor signal;

store the second foot traffic record; and

generate the recommendation for the product identified in a retail inventory listing based on the display-demographic map, wherein the display-demographic map is based on a first user profile related to the first user and a second user profile related to the second user.

10. A method for in-store customer traffic analysis, the method comprising:

receiving, from a sensor network over an electronic communications network, a first sensor signal indicating that a first user has been recognized by a first biometric sensor of the sensor network in a retail store, the first biometric sensor being associated with a first display in the retail store;

determining a first user demographic category associated with the first user based on a first user identifier within the first sensor signal;

obtaining demographic-display data associated with the first user demographic category;

determining a recommendation to be displayed in the first display based on the demographic-display data;

generating a processor-executable instruction to directional signage of the first display towards a product in the retail store according to the recommendation in an automated fashion;

determining, based on sensor data from the sensor network, a direction from which the first user approached the first display and an amount of time the first user spent within a proximity of the first display, wherein the direction is determined using a directional sensor within the sensor network;

calculating a first score based on the amount of time the first user spent within the proximity of the first display and the direction from which the first user approached the first display;

associating the first score with the first user;

storing the first score;

generating a display-demographic map indicating a correlation between the first display and the first user demographic category; and

storing the display-demographic map.

11. The method of claim 10 , further comprising generating a first foot traffic record associated with the first user based on the first sensor signal.

12. The method of claim 10 , wherein the first biometric sensor senses at least one of a face of the first user, a fingerprint of the first user, or a voice of the first user.

13. The method of claim 10 , further comprising:

obtaining a first user profile corresponding to the first user; and

identifying a demographic category based on the first user profile.

14. The method of claim 13 , further comprising;

obtaining an inventory listing associated with the retail store; and

generating the recommendation for the product contained in the inventory listing, based on the display-demographic map.

15. The method of claim 14 , further comprising:

providing the recommendation for the product contained in the inventory listing via a graphical user interface.

16. The method of claim 15 , further comprising:

obtaining a user input via the graphical user interface in response to providing the recommendation for the product contained in the inventory listing;

generating a display instruction based on the user input; and

providing the display instruction via the graphical user interface.

17. The method of claim 10 , further comprising:

updating, based on the amount of time the first user spent within the proximity of the first display, a second score indicating an interest of members of a second user demographic group associated with the first user in the first display in a time slot of a particular day.

18. The method of claim 10 , further comprising:

receiving a second sensor signal indicating that a second user has been recognized by the first biometric sensor;

extracting a second user identifier from the second sensor signal;

correlating the second sensor signal to the first display;

generating a second foot traffic record associated with the second user identifier and the first display, based on the second sensor signal;

storing the second foot traffic record; and

generating the recommendation for the product identified in a retail inventory listing based on the display-demographic map, wherein the display-demographic map is based on a first user profile related to the first user and a second user profile related to the second user.

19. A non-transitory computer readable medium storing instructions that, when executed by one or more hardware processors, configure the one or more hardware processors to perform operations comprising:

receiving, from a sensor network over an electronic communications network, a first sensor signal indicating that a first user has been recognized by a first biometric sensor of the sensor network in a retail store, the first biometric sensor being associated with at least one display in the retail store;

determining a user demographic category of the first user based on a first user identifier within the first sensor signal;

obtaining, based on an identifier of a first display, demographic-display data associated with the user demographic category, the demographic-display data indicating an interest correlation between the at least one display and the first user in a time window;

generating a processor-executable instruction for displaying a product in the first display;

determining, based on sensor data from the sensor network, a direction from which the first user approached the first display and an amount of time the first user spent within a proximity of the first display, wherein the direction is determined using a directional sensor within the sensor network;

calculating a first score based on the amount of time the first user spent within the proximity of the at least one display and the direction from which the first user approached the first display;

associating the first score with the first user identifier;

generating a display-demographic map indicating a correlation between the first display and the user demographic category; and

storing the display-demographic map.

20. The non-transitory computer readable medium of claim 19 , the operations further comprising;

receiving a second sensor signal indicating that a second user has been recognized by the first biometric sensor in the retail store;

extracting a second user identifier from the second sensor signal;

correlating the second sensor signal to the at least one display;

generating a second foot traffic record associated with the second user identifier and the at least one display, based on the second sensor signal;

storing the second foot traffic record; and

generating a recommendation for the product identified in a retail inventory listing based on the display-demographic map, wherein the display-demographic map is based on a first user profile related to the first user and a second user profile related to the second user.