Abstract: The present disclosure relates to a response prediction system that intelligently optimizes the quality of responses to a survey by predicting response quality and generating suggested changes (e.g., improving question ordering, question phrasing, question type, etc.). For example, in one or more embodiments, the response prediction system predicts response quality based on extracted survey characteristics. The response prediction system uses the predicted response quality to generate suggested changes before publishing the survey. Additionally, the response prediction system collects feedback by analyzing responses after the survey has been published to update suggested changes specific to the survey.

Abstract: This disclosure covers methods, systems, and computer-readable media that select answer choices from potential answer choices for a digital question based on responses to other digital questions and/or embedded user data. In certain embodiments, the disclosed systems select answer choices from potential answer choices for a digital question based on a multiple choice response. Furthermore, in some embodiments, the disclosed systems select answer choices from potential answer choices for a digital question based on keywords and/or sentiment values identified by analyzing a text response. In some embodiments, the disclosed systems select answer choices for a digital question from a dynamic choice reference dataset that comprises potential answer choices. Additionally, in one or more embodiments, the disclosed systems train and/or utilize a machine-learning model to select answer choices from potential answer choices for a digital question based on a response.