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作 者:刘以勇 王菁 段连园 吴德俊 王晨钊 LIU Yi-yong;WANG Jing;DUAN Lian-yuan;WU De-jun;WANG Chen-zhao(China Mobile Group Co.,Ltd.,Beijing 100032,China;China Mobile Group Design Institute Co.,Ltd.,Beijing 100080,China)
机构地区:[1]中国移动通信集团有限公司,北京100032 [2]中国移动通信集团设计院有限公司,北京100080
出 处:《电信工程技术与标准化》2024年第9期1-7,共7页Telecom Engineering Technics and Standardization
摘 要:面对增长的客户需求和期望,运营商一线客服人员解决客户问题的能力急需提升。AI技术的深度应用让更加快速、高效响应客户问题成为可能,支撑一线解决客户问题的智能化工具迅速发展,但工具存在场景化应用不足和规划缺乏体系等问题。本文旨在解决一线人员处理客户问题过程中所用工具未覆盖服务全流程、与业务场景融合度低、数智化技术应用不深等痛点。通过重新界定客户问题解决流程,识别工具痛点与一线需求差距,重新构建了工具解决方案及所需能力和相关技术,明确了5类工具及其建设与运营模式。Faced with the increasing customer demands and expectations,there is an urgent need for front-line customer service personnel in operators to enhance their ability to resolve customer issues.The deep application of AI technology has made it possible to respond to customer issues more rapidly and efficiently,leading to the swift development of intelligent tools that support front-line staffin problem-solving.However,these tools suffer from insufficient scenario-based applications and a lack of systematic planning.This study aims to address the pain points in the tools used by front-line staff,such as the incomplete coverage of the entire service process,low integration with business scenarios,and shallow application of digital intelligence technology.By redefining the customer issue resolution process,identifying the pain points and gaps in the tools relative to the needs of front-line staff,the study reconstructs the tool solutions and the required capabilities and technologies.It clarifiesfive types of tools and their construction and operation models.
分 类 号:TN915[电子电信—通信与信息系统]
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