Computers & Industrial Engineering

TLDR

Customer complaints are valuable for improving service quality and maintaining loyalty, making their collection and analysis essential for CRM. The study aims to develop an interoperable ontology and case‑based reasoning system for intelligent complaint handling. The authors construct a Web Ontology Language ontology of complaints and use it as the foundation for a case‑based reasoning system that retrieves, indexes, and compares cases via similarity matrices. The resulting system provides enterprises with a knowledge‑based, self‑learning method for systematically resolving customer complaints.

Abstract

While responding to customer complaints and solving customer problems effectively contributes to high service quality, a customer complaint can also be regarded as a critical source of information for improving the firms’ products and services. Handling complaints successfully can resolve crises and help maintain customer loyalty. Hence, from a customer relationship management (CRM) perspective, it is well worth collecting and analyzing complaint-related knowledge. Constructing ontology of customer complaints is the first crucial step in CRM. Web Ontology Language (OWL) is a formal tool for defining an ontology, providing a complete description of the domain knowledge. The ontological schema of complaint handling serves as the basis for case-based reasoning (CBR) mechanism which includes retrieving cases, using case indexing and similarity matrixes procedures. Thus, this research presents an interoperable ontology and case-based reasoning for intelligent complaint handling. The solution offers enterprises an informative and knowledge-based methodology to resolve customer complaints systematically with self-learning feature.