A Measure for Dialog Complexity and its Application in Streamlining Service Operations
This work addresses the need for efficient service operations in industries relying on customer interactions, but it appears incremental as it builds on existing dialog analysis methods.
The paper tackled the problem of analyzing customer-business dialogs in service operations by introducing a dialog complexity measure, and demonstrated its application to improve request handling and agent evaluation using public and enterprise datasets.
Dialog is a natural modality for interaction between customers and businesses in the service industry. As customers call up the service provider, their interactions may be routine or extraordinary. We believe that these interactions, when seen as dialogs, can be analyzed to obtain a better understanding of customer needs and how to efficiently address them. We introduce the idea of a dialog complexity measure to characterize multi-party interactions, propose a general data-driven method to calculate it, use it to discover insights in public and enterprise dialog datasets, and demonstrate its beneficial usage in facilitating better handling of customer requests and evaluating service agents.