While customer experience (CE) is recognized as a critical determinant of business success, both academics and managers are yet to find a means to gain a comprehensive understanding of CE cost-effectively. The authors argue that the application of relevant AI technology could help address this challenge. Employing interactively prompted narrative storytelling, and the authors investigate the effectiveness of sentiment analysis (SA) on extracting valuable CE insights from primary qualitative data generated via chatbot interviews.,Drawing on a granular and semantically clear framework for studying CE feelings, an artificial intelligence (AI) augmented chatbot was designed. The chatbot interviewed a crowdsourced sample of consumers about their recalled service experience feelings. By combining free-text and closed-ended questions, the authors were able to compare extracted sentiment polarities against established measurement scales and empirically validate our novel approach.,The authors demonstrate that SA can effectively extract CE feelings from primary chatbot data. This findings also suggest that further enhancement in accuracy can be achieved via improvements in the interplay between the chatbot interviewer and SA extraction algorithms.,The proposed customer-centric approach can help service companies to study and better understand CE feelings in a cost-effective and scalable manner. The AI-augmented chatbots can also help companies to foster immersive and engaging relationships with customers. This study focuses on feelings, warranting further research on AI's value in studying other CE elements.,The unique inquisitive role of AI-infused chatbots in conducting interviews and analyzing data in realtime, offers considerable potential for studying CE and other subjective constructs.

中文翻译：

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AI感觉到您：通过聊天机器人访谈进行的客户体验评估

尽管客户体验（CE）是企业成功的关键决定因素，但学者和管理人员都尚未找到一种方法来以成本效益的方式全面了解CE。作者认为，相关AI技术的应用可以帮助应对这一挑战。利用交互式提示叙事叙事，作者研究了情感分析（SA）在从通过聊天机器人访谈产生的主要定性数据中提取有价值的CE见解的有效性。基于人工智能的人工智能，一个细粒度且语义清晰的框架用于研究CE感受AI）增强聊天机器人的设计。聊天机器人采访了众包样本的消费者，以回顾他们回忆的服务体验。通过结合自由文本和封闭式问题，作者能够将提取的情感极性与既定的测量标准进行比较，并通过经验验证了我们的新颖方法。作者证明，SA可以有效地从主要聊天机器人数据中提取CE感受。这些发现还表明，通过改善聊天机器人访问者与SA提取算法之间的相互作用，可以进一步提高准确性。所提出的以客户为中心的方法可以帮助服务公司以成本效益高的方式研究和更好地理解CE感受。可扩展方式。AI增强型聊天机器人还可以帮助公司与客户建立沉浸式的互动关系。这项研究着重于感受，因此有必要进一步研究AI在研究其他CE要素方面的价值。