Systems and methods for the analysis of user experience testing with AI acceleration

A method for artificial intelligence (AI) assisted analysis of a user experience study comprising:

• training an AI model to detect incidents of interest, wherein the incidents of interest include user abandonment, user failure, user frustration, and delayed completion of an objective using a first training set;
• identifying the incidents of interest within a second training set;
• training the AI model to detect at least one trigger for the identified incidents of interest using the second training set;
• receiving at least one study for analysis;
• identifying the incidents of interest within the at least one study;
• receiving a query for a specific incident of interest within the study;
• selecting the trigger for the specific incident of interest using the AI model;
• and generating at least one analytics output including the selected trigger;
• wherein the analytics output includes at least one of a heat map, a clickstream, a sentiment analysis, an audio clip, a video clip, a question chart with confidence intervals, and a word cloud.