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.
%0 Journal Article
%1 ls_leimeister
%A Reinhard, Philipp
%A Li, Mahei Manhai
%A Peters, Christoph
%A Leimeister, Jan Marco
%D 2025
%E Bruhn, Manfred
%E Hadwich, Karsten
%J Forum Dienstleistungsmanagement
%K Customer_Service ITSM Process_Mining Text_Mining dempub itegpub pub_cpe pub_jml pub_mli pub_pre
%P 327-360
%R 10.1007/978-3-658-48325-8_11
%T Enhancing IT Service Management Through Process Mining – A Digital Analytics Perspective on Documented Customer Interactions
%U http://pubs.wi-kassel.de/wp-content/uploads/2025/06/JML_1028.pdf
%V Digital Analytics im Dienstleistungsmanagement
%X 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.
@article{ls_leimeister,
abstract = {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.},
added-at = {2025-06-10T11:49:35.000+0200},
author = {Reinhard, Philipp and Li, Mahei Manhai and Peters, Christoph and Leimeister, Jan Marco},
biburl = {https://www.bibsonomy.org/bibtex/2cc752ec584867afd6f0736d906de3acb/ls_leimeister},
doi = {10.1007/978-3-658-48325-8_11},
editor = {Bruhn, Manfred and Hadwich, Karsten},
interhash = {c9de50ba0eb50115c75ac4cb8d5b8190},
intrahash = {cc752ec584867afd6f0736d906de3acb},
journal = {Forum Dienstleistungsmanagement},
keywords = {Customer_Service ITSM Process_Mining Text_Mining dempub itegpub pub_cpe pub_jml pub_mli pub_pre},
pages = {327-360},
timestamp = {2025-06-11T15:38:28.000+0200},
title = {Enhancing IT Service Management Through Process Mining – A Digital Analytics Perspective on Documented Customer Interactions},
url = {http://pubs.wi-kassel.de/wp-content/uploads/2025/06/JML_1028.pdf},
volume = {Digital Analytics im Dienstleistungsmanagement},
year = 2025
}