Enhancing Auto Service Analytics: Automated Classification of Technician comments using text mining and Machine Learning

The ability to accurately classify service types from technician comments is a critical challenge for many automotive original equipment manufacturers (OEMs) that lack standardized opcode systems. Existing rule-based methods, while precise, leave numerous observations unlabeled due to variability in textual descriptions. This study proposes a novel approach that combines text mining techniques with a multinomial classification model to automate service type classification. By leveraging structured and unstructured data, this method achieves a significant improvement in classification accuracy, laying the groundwork for enhanced analytics and predictive modeling in automotive service data.