What is a virtual agent?

Virtual agents give time back to your team to focus on higher value work. A common task eliminated by using a virtual agent is triaging. IT professionals waste time tagging teammates and reassigning tickets before work can start. A virtual agent can get the right ticket to the right person at the right time. Beyond automated messaging capabilities, machine learning enables a virtual agent to communicate with your customers in a more human-like way. As soon as a ticket is created, a virtual agent starts working with your customers to get to the root of the issue. And when an issue needs escalation, the triaging and communication with teammates begin immediately.

Natural language processing (NLP) is the ability of a computer program to understand human language as it is spoken and written. Your customers will give clues to how they are feeling and the severity of the issue with the words they use in a service request. NLP lets a virtual agent determine with better accuracy the severity and sentiment. A virtual agent will use sentiment analysis to escalate issues and seamlessly transition the issue to humans who are available to help. 

Do your customers have a hotline they can call? Voice assistants can offer high levels of service by learning as much as possible about the customer and their issue before escalating to a teammate. Virtual agents elevate this experience by listening to how your customers respond and interpreting the tone of the conversation. Imagine a voice assistant that communicates the issue and the level of distress of the customer before you even pick up the phone.

Training has long been the domain of data scientists and machine learning experts. Today’s virtual agents can be trained without code or specialized knowledge. Training involves the digestion and analysis of a rule set and the creation of a model for future use. Once trained, teams should interact with the virtual agent in a sandbox environment. If you're unsatisfied with your test interactions, you can adjust and reconfigure your training data until your interactions are satisfactory. 

One of the challenges of service management is the many channels your customers use to reach you. Most service management software works to centralize service requests that originate from phone, email, text, Slack, and web channels. Teams then work on the requests and use the same service management software to communicate back to internal and external customers. What’s been missing is the software’s ability to match the tone, length, and conversational style of each third-party channel. A virtual agent solves this problem by deep integration into third-party communication channels and an intelligent understanding of how to successfully communicate in each channel. 

Conversational analytics is the study of social interactions that investigates what it takes to create mutual understanding between two parties. This branch of study has identified trends in the content and tone of conversations that we can use to better understand how satisfied our customers are. Rather than sending someone a customer satisfaction survey, conversational analytics gives you a real time look at customer satisfaction and identifies the moments where their satisfaction increases or decreases. Conversational analytics can act as an escalation tool that notifies human teammates when the virtual agent needs help. 

Google translate is great in a pinch but it is not sufficient for customer communication. Until recently, automated translation services mostly just replaced words with their translated equivalents. This created embarrassing contextual mistakes and poor communication. Using AI and NLP, virtual agents can assess the full intent of a statement and find the linguistic equivalent. A virtual agent can navigate natural language with more proficiency and allow you to serve more customers in more areas. 

The goal of a customer service agent is to understand a customer's problem, determine the severity, and gauge their emotional state. A well-trained virtual agent can quickly interpret all three. Imagine a virtual agent running a software company's service desk. An outage begins and customers immediately flood the service desk with tickets. Human customer service agents need to open each ticket before confirming they were all related. A virtual agent can do that in an instant and fast-track the escalation of the issue. 

Cold emails and lead generation are time consuming activities done by some of our most expensive employees. Imagine a world where a virtual agent is actively learning about potential customers and engaging them with personalized messaging. When the opportunity strikes in the virtual agent's communication, a human salesperson is brought in to close the deal. 

Financial professionals spend an enormous amount of time compiling documents each quarter. These documents need to be structured the same way and communicate the same information. A virtual agent can do the heavy lifting for your finance professionals freeing them to focus on the human side of financial reporting. Financial professionals are responsible for communicating results and projections to the business. A virtual agent can increase the speed and accuracy of these communications. 

HR professionals are excellent at helping employees reach their full potential. They are also tasked with annual and quarterly reporting on employee productivity and performance. If this process is software-based, it's an excellent candidate for management by virtual agents. A virtual agent communicating with managers and completing the reports helps your HR professionals focus on what they do best. The exciting part about integrating virtual agents into Jira Service Management is seeing all the ways they can be used. Customer service, sales, and HR are likely just the beginning of the effective use of virtual agents.