Systems and methods for altering user interfaces using predicted user activity

Abstract

A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions, that when executed on the one or more processors, cause the one or more processors to perform operations including: automatically customizing, based on a first state of a user, first content for a graphical user interface on an electronic device of the user; monitoring second activities of the user over a time period; identifying a second probability that the user has transitioned from the first state into a second state during the time period; determining when the second probability is above a second probability predefined threshold; and after determining the second probability to be above the second probability predefined threshold, automatically customizing, based on the second state of the user, second content for the graphical user interface on the electronic device of the user. Other embodiments are disclosed herein.

What is claimed is: 
     
         1 . A system comprising:
 one or more processors; and   one or more non-transitory computer-readable media storing computing instructions, that when executed on the one or more processors, cause the one or more processors to perform operations comprising:
 automatically customizing, based on a first state of a user, first content for a graphical user interface on an electronic device of the user; 
 monitoring second activities of the user over a time period; 
 identifying a second probability that the user has transitioned from the first state into a second state during the time period; 
 determining when the second probability is above a second probability predefined threshold; and 
 after determining the second probability to be above the second probability predefined threshold, automatically customizing, based on the second state of the user, second content for the graphical user interface on the electronic device of the user. 
   
     
     
         2 . The system of  claim 1 , wherein monitoring the second activities of the user over the time period comprises:
 using a mixed model comprising a mix of a Gaussian model and a second Markov model, and wherein the second state is related to the first state.   
     
     
         3 . The system of  claim 1 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform operations comprising:
 monitoring first activities of the user over a first time period;   identifying, using a first Markov model, a first probability of the user being in the first state;   determining when the first probability is above a first probability predefined threshold.   
     
     
         4 . The system of  claim 3 , wherein monitoring the first activities of the user over the first time period comprises:
 gathering information comprising at least one of:
 views of an item of a category of items; 
 cart adds of the item of the category of items; 
 registry adds of the item of the category of items; 
 transactions involving the item of the category of items; or 
 searches for the item of the category of items. 
   
     
     
         5 . The system of  claim 3 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform operations comprising:
 training the first Markov model to identify the first probability of the user being in the first state comprises at least one of:
 identifying one or more binary classifiers, each binary classifier of the one or more binary classifiers independently capable of identifying the first probability of the user being in the first state; or 
 identifying a multi-class classifier capable of assigning a distribution over the first probability of the user being in the first state. 
   
     
     
         6 . The system of  claim 5 , wherein the first Markov model is trained on a deep neural network. 
     
     
         7 . The system of  claim 1 , wherein automatically customizing the first content for the graphical user interface comprises:
 automatically changing one or more images on the graphical user interface to first images related to the first state.   
     
     
         8 . The system of  claim 1 , wherein automatically customizing the first content for the graphical user interface further comprises:
 automatically changing text displayed on the graphical user interface to first text related to the first state.   
     
     
         9 . The system of  claim 1 , wherein automatically customizing the first content for the graphical user interface further comprises:
 automatically altering a layout of the graphical user interface for the first state.   
     
     
         10 . The system of  claim 1 , wherein the first and second states comprise life events in a sequence of life events of the user. 
     
     
         11 . A method being implemented via execution of computing instructions configured to run at one or more processors and configured to be stored at non-transitory computer-readable media, the method comprising:
 automatically customizing, based on a first state of a user, first content for a graphical user interface on an electronic device of the user;   monitoring second activities of the user over a time period;   identifying a second probability that the user has transitioned from the first state into a second state during the time period;   determining when the second probability is above a second probability predefined threshold; and   after determining the second probability to be above the second probability predefined threshold, automatically customizing, based on the second state of the user, second content for the graphical user interface on the electronic device of the user.   
     
     
         12 . The method of  claim 11 , wherein monitoring the second activities of the user over the time period comprises:
 using a mixed model comprising a mix of a Gaussian model and a second Markov model, and wherein the second state is related to the first state.   
     
     
         13 . The method of  claim 11 , wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to perform operations comprising:
 monitoring first activities of the user over a first time period;   identifying, using a first Markov model, a first probability of the user being in the first state;   determining when the first probability is above a first probability predefined threshold.   
     
     
         14 . The method of  claim 13 , wherein monitoring the first activities of the user over the first time period comprises:
 gathering information comprising at least one of:
 views of an item of a category of items; 
 cart adds of the item of the category of items; 
 registry adds of the item of the category of items; 
 transactions involving the item of the category of items; or 
 searches for the item of the category of items. 
   
     
     
         15 . The method of  claim 13  further comprising:
 training the first Markov model to identify the first probability of the user being in the first state comprises at least one of:
 identifying one or more binary classifiers, each binary classifier of the one or more binary classifiers independently capable of identifying the first probability of the user being in the first state; or 
 identifying a multi-class classifier capable of assigning a distribution over the first probability of the user being in the first state. 
 
 
     
     
         16 . The method of  claim 15 , wherein the first Markov model is trained on a deep neural network. 
     
     
         17 . The method of  claim 11 , wherein automatically customizing the first content for the graphical user interface comprises:
 automatically changing one or more images on the graphical user interface to first images related to the first state.   
     
     
         18 . The method of  claim 11 , wherein automatically customizing the first content for the graphical user interface further comprises:
 automatically changing text displayed on the graphical user interface to first text related to the first state.   
     
     
         19 . The method of  claim 11 , wherein automatically customizing the first content for the graphical user interface further comprises:
 automatically altering a layout of the graphical user interface for the first state.   
     
     
         20 . The method of  claim 11 , wherein the first and second states comprise life events in a sequence of life events of the user.