Identifying augmented reality visuals influencing user behavior in virtual-commerce environments

A system comprising:

• a processing device;
• and
• a non-transitory computer-readable medium communicatively coupled to the processing device, wherein the processing device is configured to perform operations comprising:
• obtaining data indicating a plurality of augmented-reality visuals generated in a virtual-commerce environment and provided for view by a user;
• obtaining data indicating a user input provided by the user to generate manipulated augmented-reality visuals from the plurality of augmented-reality visuals;
• training a machine-learning algorithm usable to predict an epoch time during which users are likely to provide user inputs corresponding to a triggering user input, wherein training the machine-learning algorithm is performed using covariates generated from the user input provided by the user to generate the manipulated augmented-reality visuals;
• predicting, by the processing device, the epoch time by applying the machine-learning algorithm to the data indicating the user input;
• identifying a particular manipulated augmented-reality visual of the manipulated augmented-reality visuals that is viewed by the user at or nearest the epoch time;
• and
• storing the identified manipulated augmented-reality visual.

A non-transitory computer-readable medium storing program code executable by a processor for enhancing personalization of a virtual-commerce environment by identifying augmented-reality visual content of the virtual-commerce environment, the program code comprising:

• program code for obtaining, by the processor, data indicating a plurality of augmented-reality visuals generated in the virtual-commerce environment and provided for view by a user;
• program code for obtaining, by the processor, data indicating a user input provided by the user to generate manipulated augmented-reality visuals from the plurality of augmented-reality visuals;
• program code for training, by the processor, a machine-learning algorithm usable to predict an epoch time during which users are likely to provide user inputs corresponding to a triggering user input, wherein training the machine-learning algorithm is performed using at least one covariate generated from the user input provided by the user to generate the manipulated augmented-reality visuals;
• program code for predicting, by the processor, the epoch time by applying the machine-learning algorithm to the data indicating the user input;
• program code for identifying, by the processor, a particular manipulated augmented-reality visual of the manipulated augmented-reality visuals that is viewed by the user at or nearest the epoch time;
• and
• program code for storing, by the processor, the identified manipulated augmented-reality visual.