Our study explores the integration of text mining and process mining to enhance the understanding of IT support agents' problem-solving activities documented in service tickets. Despite the rise of AI-based self-service systems, the pressure on IT support to deliver high-quality service remains significant, necessitating advanced analytical approaches. While text mining has been used for classifying customer requests or predicting satisfaction, it falls short in revealing the actual processes agents follow. By conducting a systematic literature review and a case study, this research outlines a novel approach combining text and process mining. The findings provide practical guidance for extracting activity catalogs and generating event logs from service documentation, offering valuable insights into service processes and highlighting challenges related to data quality in digital analytics.