Abstract
Most water utilities have to handle a substantial number of customer complaints every year. Traditionally, complaints are handled by skilled staff who know how to identify primary issues, classify complaints, find solutions, and communicate with customers. The effort associated with complaint processing is often great, depending on the number of customers served by a water utility. However, the rise of natural language processing (NLP), enabled by deep learning, and especially the use of deep recurrent and convolutional neural networks, has created new opportunities for comprehending and interpreting text complaints. As such, we aim to investigate the value of the use of NLP for processing customer complaints. Through a case study about the Water Utility Groningen in the Netherlands, we demonstrate that NLP can parse language structures and extract intents and sentiments from customer complaints. As a result, this study represents a critical and fundamental step toward fully automating consumer complaint processing for water utilities.
Highlights
Water utilities often consider customer complaints to be a valuable source of information for identifying system malfunctions and improving their services
We aim to identify the value of natural language processing (NLP) in processing customer complaints about water problems in this case study by investigating whether an NLP model can understand the syntactic meanings of words in a particular context, classify a customer complaint correctly, identify the customer’s emotion in the complaint, and recognize the intent and request mentioned in the complaint
We demonstrated that natural language processing, as an interdisciplinary field combining linguistics and deep learning, is an effective tool for automating text processing
Summary
Water utilities often consider customer complaints to be a valuable source of information for identifying system malfunctions and improving their services. The essential information abstracted from verbal communication can only be recorded concisely This can occasionally result in misunderstandings and requires water utilities to maintain an adequate number of telephone operators to handle incoming calls, during rush hours or in the event of a malfunction affecting a larger area. An increasing number of (Dutch) water utilities have put an online system in place for customers to submit complaints (see Appendix A). This enables information to be stored in a more organized and efficient manner. While complaints tend to be collected digitally, their content still needs to be processed manually—e.g., extracting critical information, classifying the major issue, and responding to the customer with a solution
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