Which Channel to Ask My Question? Personalized Customer Service Request Stream Routing using Deep Reinforcement Learning

Customer services are critical to all companies, as they may directly connect to the brand reputation. Due to a great number of customers, e-commerce companies often employ multiple communication channels to answer customers' questions, for example, chatbot and hotline. On one hand, each channel has limited capacity to respond to customers' requests, on the other hand, customers have different preferences over these channels. The current production systems are mainly built based on business rules, which merely considers tradeoffs between resources and customers' satisfaction. To achieve the optimal tradeoff between resources and customers' satisfaction, we propose a new framework based on deep reinforcement learning, which directly takes both resources and user model into account. In addition to the framework, we also propose a new deep-reinforcement-learning based routing method-double dueling deep Q-learning with prioritized experience replay (PER-DoDDQN). We evaluate our proposed framework and method using both synthetic and a real customer service log data from a large financial technology company. We show that our proposed deep-reinforcement-learning based framework is superior to the existing production system. Moreover, we also show our proposed PER-DoDDQN is better than all other deep Q-learning variants in practice, which provides a more optimal routing plan. These observations suggest that our proposed method can seek the trade-off where both channel resources and customers' satisfaction are optimal.Comment: 13 pages, 7 figure

A Question Detection Algorithm for Text Analysis

In this paper, an effective question detection algorithm for Vietnamese text analysis is proposed. The proposed algorithm takes an audio file as input, converts its speech to text, and returns question detection result. This is extremely useful for a text analyzer to determine if a given sentence generated from an audio file is a question or not, particularly in chatbot or voicebot systems where very often there are needs for automatic replies to questions queried by users. The algorithm uses two tiers of question words and a customized question phrases to achieve 88.64 % accuracy on a sub-dataset of 176 questions prepared based on FPT Open Speech Dataset. © 2020 ACM.The authors would thank FPT University and Ural Federal University for supporting this research. In addition, the authors would thank the students: Nguyen Khuong Quan, Tran Viet Thai, Le Sy Thanh Long in SE1402 class, FPT University for their partial support this research

Arrive as guests and leave as friends : the role of hedonic experiences in the luxury context

This research was conducted to understand the role of personalized customer service in the customers’ hedonic experiences. A main objective was imposed in the research to fathom the relationship between the two factors, being made research the spectrum of luxury hospitality from the perspective of managers and customers. The purpose of the study falls under the principle that customer service is the key to a successful business. Twenty interviews were conducted with people on both sides of the coin – employees and guests – answering open-ended questions regarding the topic. In conclusion, it was found that personalized customer service undoubtedly impacts the guest's hedonic experience. Moreover, employees who are at the center of this effect play a major role in the overall hedonic experience.Esta investigação foi conduzida para compreender o papel do serviço personalizado ao cliente nas experiências hedónicas dos hóspedes. Um objetivo principal impôs-se na pesquisa para compreender a relação entre os dois fatores, sendo feita a pesquisa no espectro da hotelaria de luxo na perspetiva de managers e clientes. O objetivo do estudo enquadra-se no princípio de que o serviço ao cliente é a chave para um negócio bem sucedido. Foram realizadas entrevistas a vinte pessoas - empregados e hóspedes - respondendo a perguntas abertas sobre o tema. Concluindo, constatou-se que o serviço personalizado ao cliente sem dúvida impacta a experiência hedónica do hóspede. Além disso, quem está no centro desse efeito são os funcionários que desempenham um papel crucial na experiência hedónica geral