A novel framework for customer complaint management

Abstract

Complaining is one option available to customers to express their dissatisfaction with inadequate services. Their complaints contain valuable information for service providers to improve customer relationships and operational quality, which can ultimately enhance business profitability. Customer complaints are frequently handled at the individual level, however, which addresses the symptoms rather than the causes of customer dissatisfaction. This paper presents a framework integrating a decision tree approach, a common data mining tool, into Six Sigma methodology to analyze customer complaints in aggregate and improve service quality by identifying and addressing the underlying causes of failed service. A case study of a restaurant chain was used to demonstrate the effectiveness of the proposed framework. The results indicated a significant (60%) decrease in the number of customer complaints received. Subsequent long-term benefits can be expected.

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