Systems and methods for pre-communicating shoppers' communication preferences to retailers

Abstract

Systems and methods are provided for providing a customized user experience. Providing a customized user experience may include receiving, from a graphical user interface displayed on a mobile device a user input indicative of a preferred level of interaction by the user, and monitoring, by a sensor, a facial expression of the user. Then, a first preference metric may be assigned to the user based on the monitored facial expression. Providing a customized user experience may further include monitoring, by a sensor, a behavior of the user, assigning a second preference metric based on the monitored behavior, and aggregating at least the user input, the first preference unit, and the second preference metric to generate a preference score of the user. The preference score may be stored in a central database, displayed on a remote device, and used to modify a customer service experience.

1 - 20 . (canceled) 
     
     
         21 . A computer-implemented method of providing a customized user experience, the method comprising:
 receiving, from a first device, a plurality of electromagnetic signals generated by a plurality of sensors, the first device being associated with a user;   determining, by a processor, using triangulation, a movement of the user based on:
 strengths of the received electromagnetic signals; and 
 locations of the sensors; 
   requesting, by a second device, a history of a plurality of transactions associated with the user;   requesting, by the second device, a first preference score associated with the user, the first preference score being stored in a central database;   determining, by an image sensor positioned on the second device, an emotion metric of the user, wherein determining the emotion metric of the user comprises:
 recording a video of the user; 
 separating the video into a plurality of frames; and 
 processing the frames, by a machine-learning algorithm, to match the frames to one of a plurality of user emotions; 
   varying the first preference score based on the emotion metric of the user to generate a second preference score, wherein varying the first preference score comprises:
 varying the first preference score to generate the second preference score that is more indicative of preferring more interaction based on the history of the plurality of transactions associated with the user if the emotion metric indicates positive emotion after interaction, wherein the second preference score is higher than the first preference score; or 
 varying the first preference score to generate the second preference score that is more indicative of preferring less interaction based on the history of the plurality of transactions associated with the user if the emotion metric indicates negative emotion after interaction, wherein the second preference score is lower than the first preference score; and 
   displaying the second preference score on at least one of the first device or the second device.   
     
     
         22 . The method of  claim 21 , wherein the first device and the second device each comprise at least one of a smartphone, a tablet, a wearable device, or a virtual reality headset. 
     
     
         23 . The method of  claim 21 , wherein the sensors comprise at least one Bluetooth low-energy beacon, at least one RFID device, and at least one camera. 
     
     
         24 . The method of  claim 23 , further comprising:
 receiving facial expression data associated with the user from the sensors; and   varying the first preference score based on the facial expression data of the user to generate the second preference score.   
     
     
         25 . The method of  claim 21 , wherein the sensors comprise at least one wireless sensor. 
     
     
         26 . The method of  claim 21 , wherein the second preference score is based on at least a user input indicative of the user's preferred level of interaction. 
     
     
         27 . The method of  claim 21 , wherein the history of the plurality of transactions comprises at least one of:
 credit history, purchase history, product history, merchant history, the transactions made by the user, locations and merchants at which the transactions were made, date and time at which the transactions were made, amounts of customer interaction prior to making the transactions, amount of the transactions made, time spent before making the transactions, or degrees of assistance received before making the transactions.   
     
     
         28 . The method of  claim 21 , wherein the second preference score is based on a degree of customer service assistance to be offered to the user. 
     
     
         29 . The method of  claim 27 , further comprising:
 aggregating the transaction history, the movement of the user, and the emotion metric of the user; and   modifying the first preference score based on the aggregation.   
     
     
         30 . The method of  claim 21 , further comprising:
 recording, by a microphone, a voice of the user; and   modifying the first preference score based on the recorded voice.   
     
     
         31 . A system for providing a customized user experience, comprising:
 at least one memory storing instructions; and   at least one processor executing the instructions to perform operations comprising:
 receiving, from a first device, a plurality of electromagnetic signals generated by a plurality of sensors, the first device being associated with a user; 
 determining, by a processor using triangulation, a movement of the user based on:
 strengths of the received electromagnetic signals; and 
 locations of the sensors; 
 
 requesting, by a second device, a history of a plurality of transactions associated with the user; 
 requesting, by the second device, a first preference score associated with the user, the first preference score being stored in a central database; 
 determining, by an image sensor positioned on the second device, an emotion metric of the user, wherein determining the emotion metric of the user comprises:
 recording a video of the user; 
 separating the video into a plurality of frames; and 
 processing the frames, by a machine-learning algorithm, to match the frames to one of a plurality of user emotions; 
 
 varying the first preference score based on the emotion metric of the user to generate a second preference score, wherein varying the first preference score comprises:
 varying the first preference score to generate the second preference score that is more indicative of preferring more interaction based on the history of the plurality of transactions associated with the user if the emotion metric indicates positive emotion after interaction, wherein the second preference score is higher than the first preference score; or 
 varying the first preference score to generate the second preference score that is more indicative of preferring less interaction based on the history of the plurality of transactions associated with the user if the emotion metric indicates negative emotion after interaction, wherein the second preference score is lower than the first preference score; and 
 
 displaying the second preference score on at least one of the first device or the second device. 
   
     
     
         32 . The system of  claim 31 , wherein the first device and the second device each comprise at least one of a smartphone, a tablet, a wearable device, or a virtual reality headset. 
     
     
         33 . The system of  claim 31 , wherein the sensors comprise at least one Bluetooth low-energy beacon, at least one RFID device, and at least one camera. 
     
     
         34 . The system of  claim 33 , wherein the operations further comprise:
 receiving facial expression data associated with the user from the sensors; and   varying the first preference score based on the facial expression data of the user to generate the second preference score.   
     
     
         35 . The system of  claim 31 , wherein the sensors comprise at least one wireless sensor. 
     
     
         36 . The system of  claim 31 , wherein the second preference score is based on at least a user input indicative of the user's preferred level of interaction. 
     
     
         37 . The system of  claim 31 , wherein wherein the history of the plurality of transactions the transaction history comprises at least one of:
 credit history, purchase history, product history, merchant history, the transactions made by the user, locations and merchants at which the transactions were made, date and time at which the transactions were made, amounts of customer interaction prior to making the transactions, amount of the transactions made, time spent before making the transactions, or degrees of assistance received before making the transactions.   
     
     
         38 . The system of  claim 31 , wherein the second preference score is based on a degree of customer service assistance to be offered to the user. 
     
     
         39 . The system of  claim 31 , wherein the operations further comprise:
 recording, by a microphone, a voice of the user; and   modifying the first preference score based on the recorded voice.   
     
     
         40 . A non-transitory computer-readable medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform operations comprising:
 receiving, from a first device, a plurality of electromagnetic signals generated by a plurality of sensors, the first device being associated with a user;   determining, by a processor using triangulation, a movement of the user based on:
 strengths of the received electromagnetic signals; and 
 locations of the sensors; 
   receiving facial expression data associated with the user from the plurality of sensors;   requesting, by a second device, a history of a plurality of transactions associated with the user;   requesting, by the second device, a first preference score associated with the user, the first preference score being stored in a central database;   determining, by an image sensor positioned on the second device, an emotion metric of the user, wherein determining the emotion metric of the user comprises:
 recording a video of the user; 
 separating the video into a plurality of frames; and 
 processing the frames, by a machine-learning algorithm, to match the frames to one of a plurality of user emotions; 
   varying the first preference score to generate a second preference score based on at least one of:
 the movement of the user; 
 the received facial expression data; or 
 the determined emotion metric of the user; 
 wherein varying the first preference score comprises:
 varying the first preference score to generate the second preference score that is more indicative of preferring more interaction based on the history of the plurality of transactions associated with the user if the emotion metric indicates positive emotion after interaction, wherein the second preference score is higher than the first preference score, or 
 varying the first preference score to generate the second preference score that is more indicative of preferring less interaction based on the history of the plurality of transactions associated with the user if the emotion metric indicates negative emotion after interaction, wherein the second preference score is lower than the first preference score; and 
 
   displaying the second preference score on at least one of the first device or the second device.