Zendesk, Inc.
AUTOMATICALLY SUGGESTING MACROS TO HELP AGENTS PROCESS TICKETS IN AN ONLINE CUSTOMER-SUPPORT SYSTEM

Abstract:

We have developed a system that automatically suggests macros to help customer-support agents process customer-support tickets in an online customer-support system. During operation, the system receives a customer-support ticket, which is associated with a request from a customer in the customer-support system, wherein the request relates to a product or a service used by the customer. Next, the system converts text from the customer-support ticket into a ticket embedding in a vector space. The system then feeds the ticket embedding into a macro-suggestion model, which correlates ticket embeddings with macros, wherein each of the macros comprises a sequence of commands that performs an operation to facilitate processing of the customer-support ticket. If the macro-suggestion model produces suggested macros, the system presents the suggested macros to a customer-support agent. When the customer-support agent selects a suggested macro, the system facilitates application of the selected macro to the customer-support ticket.