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

Abstract

The disclosed embodiments generally relate to in-store customer traffic analysis systems and methods. The system includes at least one sensor positioned within a retail store, at least one display associated with the at least one sensor, one or more memory devices storing instructions and one or more hardware processors configured to execute the instructions to perform operations. The operations include receiving a sensor signal indicating that a user device is within a proximity to the at least one sensor in the retail store, extracting a user device identifier from the sensor signal, correlating the sensor signal to the at least one display, generating a foot traffic record associated with the user device identifier and the at least one display, based on the received sensor signal, and storing the generated foot traffic record.

What is claimed is: 
     
         1 . An analysis system, comprising:
 a sensor network comprising a plurality of sensors, the plurality of sensors comprising a first sensor of a first type and a second sensor of a second type;   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 category associated with the first user; 
 obtain display data associated with the first user category; 
 determine a recommendation to be displayed in a first display based on the display data; 
 generate a processor-executable instruction to modify directional signage of the first display towards an item 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 the second 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; 
 generate, based on the first score, a display map indicating a correlation between the first display and the first user category; and 
 store the display map. 
   
     
     
         2 . The analysis 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 analysis 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 analysis 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 category based on the first user profile.   
     
     
         5 . The analysis system of  claim 4 , wherein the one or more hardware processors are further configured to execute instructions to:
 obtain an inventory listing associated with a retail store; and   generate the recommendation for a product contained in the inventory listing, based on the display map.   
     
     
         6 . The analysis 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 analysis 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 analysis 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 analysis 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 a product identified in a retail inventory listing based on the display map, wherein the display 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 customer traffic analysis, the method comprising;
 receiving, from a sensor network comprising a first sensor of a first sensor type and a second sensor of a second sensor type over an electronic communications network, a first sensor signal indicating that a first user has been recognized by the first sensor;   determining, based on a first user identifier within the first sensor signal, a first user category associated with the first user;   obtaining display data associated with the first user category;   determining a recommendation to be displayed in a first display based on the display data;   generating a processor-executable instruction to modify directional signage of the first display towards an item according to the recommendation;   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 the second 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;   generating, based on the first score, a display map indicating a correlation between the first display and the first user category; and   storing the display 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 sensor is a biometric sensor that 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 a retail store; and   generating the recommendation for a product contained in the inventory listing, based on the display 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 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 a product identified in a retail inventory listing based on the display map, wherein the display 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, causes the one or more hardware processors to perform operations comprising:
 receiving, from a sensor network comprising a first sensor of a first sensor type and a second sensor of a second sensor type over an electronic communications network, a first sensor signal indicating that a first user has been recognized by the first sensor;   determining, based on a first user identifier within the first sensor signal, a first user category associated with the first user;   obtaining display data associated with the first user category;   determining a recommendation to be displayed in a first display based on the display data;   generating a processor-executable instruction to modify directional signage of the first display towards an item according to the recommendation;   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 the second 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;   generating, based on the first score, a display map indicating a correlation between the first display and the first user category; and   storing the display 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 sensor in a retail store;   extracting a second user identifier from the second sensor signal;   correlating the second sensor signal to 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 recommending a product identified in a retail inventory listing based on the display map, wherein the display map is based on a first user profile related to the first user and a second user profile related to the second user.