Machine-learning models for generating emerging user segments based on attributes of digital-survey respondents and target outcomes

Abstract

The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a specially trained machine-learning model to generate an emerging user segment based on a target outcome for digital survey responses and respondent attributes of respondents to such digital surveys. In some cases, for instance, the emerging user segment includes a group of users that share the same or similar characteristics as the subset of respondents. By analyzing respondent attributes of digital survey respondents that match a target outcome, the disclosed systems can use the specially trained machine-learning model to dynamically predict users that likely have (or are at risk of having) the same or a similar target outcome—even if such users did not respond to the relevant digital survey.