Chatbot de Suporte para Plataforma de Marketing Multicanal

E-goi is an organization which provides automated multichannel marketing possibilities. Given its system’s complexity, it requires a not so smooth learning curve, which means that sometimes costumers incur upon some difficulties which directs them towards appropriate Costumer Support resources. With an increase in the number of users, these Costumer Support requests are somewhat frequent and demand an increase in availability in Costumer Support channels which become inundated with simple, easily-resolvable requests. The organization idealized the possibility of automating significant portion of costumer generated tickets with the possibility of scaling to deal with other types of operations. This thesis aims to present a long-term solution to that request with the development of a chatbot system, fully integrated with the existing enterprise modules and data sources. In order to accomplish this, prototypes using several Chatbot management and Natural Language Processing frameworks were developed. Afterwards, their advantages and disadvantages were pondered, followed by the implementation of its accompanying system and testing of developed software and Natural Language Processing results. Although the developed overarching system achieved its designed functionalities, the master’s thesis could not offer a viable solution for the problem at hand given that the available data could not provide an intent mining model usable in a real-world context.A E-goi é uma organização que disponibiliza soluções de marketing digital automatizadas e multicanal. Dada a complexidade do seu Sistema, que requer uma curva de aprendizagem não muito suave, o que significa que os seus utilizadores por vezes têm dificuldades que os levam a recorrer aos canais de Apoio ao Cliente. Com um aumento de utilizadores, estes pedidos de Apoio ao Cliente tornam-se frequentes e requerem um aumento da disponibilidade nos canais apropriados que ficam inundados de pedidos simples e de fácil resolução. A organização idealizou a possibilidade de automatizar uma porção significativa de tais pedidos, podendo escalar para outro tipo de operações. Este trabalho de mestrado visa apresentar uma proposta de solução a longo prazo para este problema. Pretende-se o desenvolvimento de um sistema de chatbots, completamente integrado com o sistema existente da empresa e variadas fontes de dados. Para este efeito, foram desenvolvidos protótipos de várias frameworks para gestão de chatbots e de Natural Language Processing, ponderadas as suas vantagens e desvantagens, implementado o sistema englobante e realizados planos de testes ao software desenvolvido e aos resultados de Natural Language Processing. Apesar do sistema desenvolvido ter cumprido as funcionalidades pelas quais foi concebido, a tese de mestrado não foi capaz de obter uma solução viável para o problema dado que com os dados disponibilizados não foi possível produzir um modelo de deteção de intenções usável num contexto real

Towards Intelligent Chatbots for Customer Care - Practice-Based Requirements for a Research Agenda

Chatbots bare a great potential to save efforts and costs in customer care through service automation. Current results are however still at an early stage in functionality and not widely attainable. Here, developing a new form of intelligent chatbots is a current challenge still under review. While there have been numerous proposals for future work, virtually all agenda-setting contributions are solely based on scientific literature. This is unsatisfactory from both an academic and practical perspective, as the industrial view on the future of chatbots seems to be neglected. Therefore, this work explores how professional experts see the future of intelligent chatbots for customer care and suggests how practice can guide research based on an expert panel with 17 industrial partners. Our work identifies research opportunities based on the demands and views of key practitioners by pin-pointing expected trends. Furthermore, based on the expert opinions, we derive guidelines for organizations which state key factors that should be considered in the development or adoption of chatbots in customer care

User satisfaction of chatbot system

Abstract. The purpose of this study was to identify how the research trend of user satisfaction of chatbots in customer services is presented. As the recent raise of attention in chatbots system, especially in commercial use, the user satisfaction should be considered. The main research question was how is the topic of user satisfaction of chatbot system in customer service presented in the prior academic research? Therefore, it was distributed into 3 sub-questions; how did the amount of research change according to time? How and why did the researchers conduct the research? How did the existing literature evaluate the user satisfaction? Systematic mapping study research methodology was applied in the study. This research methodology considered the prior literature as primary studies then categorized them in order to get answer to research question. The results were how frequency the research had been published based on different scheme. 26 articles were involved as primary studies. The schemes included year of publication, research approach and user satisfaction evaluation approach. The main contribution of this study was to discover trend regarding user satisfaction of chatbot in customer service context. This would help structure academic research area and motivate future research as well as being a guidance for conducting new research. The studied proved that the topic was still received a lot of interest from researchers as number of literatures regarding topic were growing. However, the results also stated that there was still lacking of research in some area or in specific scheme. As this study’s goal is to discover the research trend in order to identify the research gap, the future research is encouraged regarding the gap identified as well as the improvement of this study

Application of Text Analytics in Public Service Co-Creation: Literature Review and Research Framework

The public sector faces several challenges, such as a number of external and internal demands for change, citizens' dissatisfaction and frustration with public sector organizations, that need to be addressed. An alternative to the traditional top-down development of public services is co-creation of public services. Co-creation promotes collaboration between stakeholders with the aim to create better public services and achieve public values. At the same time, data analytics has been fuelled by the availability of immense amounts of textual data. Whilst both co-creation and TA have been used in the private sector, we study existing works on the application of Text Analytics (TA) techniques on text data to support public service co-creation. We systematically review 75 of the 979 papers that focus directly or indirectly on the application of TA in the context of public service development. In our review, we analyze the TA techniques, the public service they support, public value outcomes, and the co-creation phase they are used in. Our findings indicate that the TA implementation for co-creation is still in its early stages and thus still limited. Our research framework promotes the concept and stimulates the strengthening of the role of Text Analytics techniques to support public sector organisations and their use of co-creation process. From policy-makers' and public administration managers' standpoints, our findings and the proposed research framework can be used as a guideline in developing a strategy for the designing co-created and user-centred public services

Contributions to chatbots and digital analytics in industry

Diese kumulative Dissertation umfasst zehn wissenschaftliche Artikel, die zur Forschung digitaler Analytik, Messung von Technologieakzeptanz und Chatbots beitragen. Ziel der Artikel ist es, die Entwicklung, Implementierung und Verwaltung von Technologien zu vereinfachen und zu unterstützen. Modelle werden entwickelt, welche die wichtigsten Schritte beschreiben und unter anderem relevante damit zusammenhängende Fragen auflisten, die zu beteiligenden Interessengruppen benennen und geeignete Tools vorstellen, welche berücksichtigt werden sollten. Es werden Chatbot Taxonomien entwickelt und vorgestellt, welche die Bandbreite der derzeit bestehenden Gestaltungsmöglichkeiten aufzeigen, während identifizierte Archetypen zu beobachtende Kombinationen aufzeigen. Die Identifizierung der häufigsten Gründe für Misserfolge und die Entwicklung kritischer Erfolgsfaktoren tragen ebenfalls zu dem Ziel bei, den Entwicklungs- und Managementprozess zu erleichtern. Da die Endnutzer über die Akzeptanz und Nutzung und damit über den Erfolg einer Technologie entscheiden, werden Ansätze genutzt, wie die Nutzerakzeptanz von Technologien gemessen werden kann und wie Nutzer frühzeitig in den Entwicklungsprozess eingebunden werden können