In some examples, a server may determine that a case, created to address an issue of a computing device, is closed and perform an analysis of a communication session between a user and a technician and the steps taken by the technician to resolve the issue. Machine learning may be used on results of the analysis to predict potential pain points. For example, steps that take longer than average and during which particular words spoken by the user increase in pitch and/or volume may be predicted to be potential pain points. The machine learning may create questions for inclusion in a custom survey based on the potential pain points. The custom survey may be presented to the user. The answers may be correlated with the potential pain points to determine actual pain points in the steps taken to resolve the issue.