A review of natural language processing in contact centre automation

被引:0
|
作者
Shariq Shah
Hossein Ghomeshi
Edlira Vakaj
Emmett Cooper
Shereen Fouad
机构
[1] Birmingham City University,Research, Innovation, Enterprise, Employability (RIEE)
[2] Birmingham City University,School of Computing and Digital Technology
[3] Aston University,School of Informatics and Digital Engineering
关键词
Contact centres (CCs); Natural language processing (NLP); Automation; Machine learning (ML);
D O I
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中图分类号
学科分类号
摘要
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 recommendations for overcoming them, ultimately expediting the pace of contact centre automation.
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页码:823 / 846
页数:23
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