USE CASE GUIDE Optimizing your customer contact center, even when everyone is working Speed resolution with machine learning Automate case categorization, from home prioritization, and assignment. Even before the pandemic completely changed the notion of a "customer contact Give agents full control center," they were a complex environment with many competing priorities. Now with Connect multiple systems into a agents working from home, there is even more of a need for tighter processes. single pane of glass. Companies using Customer Service Management can ensure they are delivering a seamless customer experience powered by modern, efficient technology, no matter Stay on top of SLAs where that service agent sits. Set SLAs for products, contracts, When a customer contacts customer service (regardless of channel–telephone, or customers and violations are a email, chat, or others), Predictive Intelligence uses machine learning to categorize, thing of the past. prioritize, and assign cases to customer service agents like Chris. Other work items Connect customer service to the like chats are automatically assigned to Chris and other agents based on their organization availability, capacity, and optionally, skills using work item queues, routing conditions, and assignment criteria. Work with other departments to quickly identify and address the root cause of customer issues. Identify and respond to major issues quickly Monitor systems and processes or use analytics to quickly identify problems and a昀昀ected customers, then keep internal teams and customers in the loop from identi昀椀cation to resolution. Incoming cases are automatically assigned to agents using Advanced Work Assignment. Chris’ work is streamlined because Agent Workspace o昀昀ers a single 360-degree view of work-in-progress. This translates into several bene昀椀ts: a shorter period to get new agents productive, elimination of the “swivel chair” syndrome of accessing multiple tools, and a seamless hando昀昀 of customers from Virtual Agent and third-party CTI providers directly to Chris and other agents. In the backend, Customer Service Management helps consolidate multiple, disconnected (and redundant) systems. Agent Assist, powered by machine learning, suggests possible solutions to Chris it 昀椀nds in the knowledge base, online community, and even other cases. For many companies, Service Level Agreements (SLAs) are an important part of delivering service–and missing them can have big consequences. From tracking SLAs on a per-customer basis to driving actions across teams with work昀氀ow to solve issues rapidly, Customer Service Management ensures Chris doesn’t miss deadlines. 3