Modeling, profiling, analysing and understanding of users are becoming increasingly important in many industries also thanks to the support of artificial intelligence, representing a key to success in today’s data-driven world. The aim of the paper is to examine the interactions that occurred between ANAS users and the company’s’ chatbot, in order to highlight the requests, preferences and needs of users and the automated response and support capabilities that are provided to them. To meet the objectives of the research, a qualitative-quantitative study was carried out, including hermeneutic analysis and an automated analysis of the conversations were realized, using a natural language analysis (NLP) tool.   The results show that the conversational material is characterized by being a precious source of information to better understand the needs of the audience and, at the same time, to be able to improve the service offered to the customer. Understanding users, their profile, key issues and requests can help companies personalize their services and adapt strategies from the bottom up. This knowledge of users’ needs can be used to increase their satisfaction and help them find the right answer more quickly and easily, as well as - as has been done - identify aspects to integrate and/or modify for a more effective and efficient communication channel responsive to user needs. Beyond the content, the form of the conversations can represent a further area for improvement. In this sense, important practical implications emerged from the data for artificial intelligence designers and corporate communication professionals working in ANAS.  

The Adoption of Chatbot for Customer Service

Monaco, Salvatore
2024-01-01

Abstract

Modeling, profiling, analysing and understanding of users are becoming increasingly important in many industries also thanks to the support of artificial intelligence, representing a key to success in today’s data-driven world. The aim of the paper is to examine the interactions that occurred between ANAS users and the company’s’ chatbot, in order to highlight the requests, preferences and needs of users and the automated response and support capabilities that are provided to them. To meet the objectives of the research, a qualitative-quantitative study was carried out, including hermeneutic analysis and an automated analysis of the conversations were realized, using a natural language analysis (NLP) tool.   The results show that the conversational material is characterized by being a precious source of information to better understand the needs of the audience and, at the same time, to be able to improve the service offered to the customer. Understanding users, their profile, key issues and requests can help companies personalize their services and adapt strategies from the bottom up. This knowledge of users’ needs can be used to increase their satisfaction and help them find the right answer more quickly and easily, as well as - as has been done - identify aspects to integrate and/or modify for a more effective and efficient communication channel responsive to user needs. Beyond the content, the form of the conversations can represent a further area for improvement. In this sense, important practical implications emerged from the data for artificial intelligence designers and corporate communication professionals working in ANAS.  
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/485948
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