A review of natural language processing in contact centre automation
Shah, Shariq and Ghomeshi, Hossein and Vakaj, Edlira and Cooper, Emmett and Fouad, Shereen (2023) A review of natural language processing in contact centre automation. Pattern Analysis and Applications. ISSN 1433-7541
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Abstract
Contact centres have been highly valued by organizations for a long time. However, the COVID-19 pandemic has highlighted their critical importance in ensuring business continuity, economic activity, and quality customer support. The pandemic has led to an increase in customer inquiries related to payment extensions, cancellations, and stock inquiries, each with varying degrees of urgency. To address this challenge, organizations have taken the opportunity to re-evaluate the function of contact centres and explore innovative solutions. Next-generation platforms that incorporate machine learning techniques and natural language processing, such as self-service voice portals and chatbots, are being implemented to enhance customer service. These platforms offer robust features that equip customer agents with the necessary tools to provide exceptional customer support. Through an extensive review of existing literature, this paper aims to uncover research gaps and explore the advantages of transitioning to a contact centre that utilizes natural language solutions as the norm. Additionally, we will examine the major challenges faced by contact centre organizations and offer recom
Item Type: | Article |
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Identification Number: | 10.1007/s10044-023-01182-8 |
Dates: | Date Event 14 June 2023 Accepted 29 June 2023 Published Online |
Uncontrolled Keywords: | Contact centres (CCs), Natural language processing (NLP), Automation, Machine learning (ML) |
Subjects: | CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science |
Divisions: | Faculty of Computing, Engineering and the Built Environment > College of Computing |
Depositing User: | Gemma Tonks |
Date Deposited: | 17 Jul 2023 15:29 |
Last Modified: | 17 Jul 2023 15:29 |
URI: | https://www.open-access.bcu.ac.uk/id/eprint/14611 |
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