Abstract
Managing customer complaints is a very challenging activity, especially when it comes to a government entity like Roads a Transport Authority (RTA) that manages the roads infrastructure and services. RTA for the management of the customer complaints requires a sophisticated and intelligent responsive system for the large volume of cases and calls, which result in needs to a lot of human resources to receive, record and handle customer calls and cases. "The key customer-save course of action is the complaints-handling process. Customers who complain to service providers and are well treated by the process are less likely to churn than customers who have no cause for complaint. In other words, a well-designed, easy-to-engage and the responsive complaints-handling process can build loyalty." (Buttle, 2016) Knowing how essential to have a well-designed complaint management system, organizations work to leverage the advantages of technologies enhancement to efficiently manage customer cases with minimal resources utilization. The critical success for that is the utilization of the most valuable asset to the organization (customer complaint data). The data gets its increasing values with the advancement of data analytics and its application in recent year. For many organizations, the data analytics usage does not go beyond the traditional descriptive analysis that describes what happened and take the necessary corrective action. Although there were a lot of attempts and research to utilize machine learning algorithms to classify customer complaints, most of falls in the area of sentiments analysis or high level topic molding identifying customer feelings or deciding what topic he/she is talking or complaining about. Actually, organization such RTA needs more that, it is the time to optimize the benefit of using Artificial Intelligence power in operational system beyond the high level text classification. The real need for RTA is to equip complaint management system with AI algorithms that help in classifying and auto-assigning the complaint to the respective department based directly without the need for human intervention. The advantage RTA has is that, it has implemented an important change in complaint management system by classifying (labeling) most of the common scenarios of complaints based on the historical data which paves the way to the use of AI-Text Classification algorithms. This project is an attempt to extend the benefits of data analytics to help not only in understanding the customer's pain points but also to help in managing customer complaints end to end using the application of machine learning and artificial intelligence.
Publication Date
5-17-2020
Document Type
Master's Project
Student Type
Graduate
Degree Name
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Advisor
Sanjay Modak
Advisor/Committee Member
Ioannis Karamitsos
Recommended Citation
Mohammed, Muammar Nasser Saleh, "Customer Complaints Auto-assignment using Machine Learning Algorithms" (2020). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/10920
Campus
RIT Dubai