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Erika Troconis-Rodell | September 26, 2019

What is a Virtual Agent and What Can it Do for the User Experience?

What is a Virtual Agent?

A virtual agent is, as described by Chatbots.org, "... a computer generated, animated, artificial intelligence virtual character that serves as an online customer service representative. It leads an intelligent conversation with users, responds to their questions and performs adequate non-verbal behavior.”

Click here to learn how virtual agents and knowledge management   can improve your user experience.


In other words, if you have ever used online customer support to resolve an issue with your phone bill or chatted with a service desk agent at your job to reset a password, then you most likely interacted with a virtual agent.

A shorter definition by TechTarget explains that "a virtual agent is a program based in artificial intelligence (AI) that provides automated customer service.” This concept, however, should not be confused with call center agents that work remotely, who can also be called “virtual agents”.

Essentially, this technology can provide basic information to customers or employees, help guide the users through questions, and automatically reroute complex conversations or issues to an actual human agent if needed. 

Uses of a Virtual Agent

It is no secret that one of the main uses for virtual agents is to automate processes and reduce workload for support agents. Two common places to do this is in customer service and in the IT service desk.

In Customer Service

From providing insights about a product order to automatically cancelling a financial transaction and issuing a refund, agents can provide customers with all the information they need so your customer service agents can dedicate more time to work complex issues.

Many retailers like 1-800-Flowers.com are now using virtual bots to assist customers during the buyer’s journey. Through the use of artificial intelligence (AI), which we will discuss later in this blog, the agents can study the customer’s behaviors and dislikes in order to personalize the experience during the buying process. They can then give customers product suggestions or recommendations and assist with tasks, such as we see in the image below.

Examples of Virtual Agent Capabilities in Customer Service

Source: https://cdn.ttgtmedia.com/rms/onlineImages/crm-virtual_agent_desktop.jpg

In the IT Service Desk

Similar to customer service, virtual agents can be used to help reduce the ticket volume of the IT service desk and help provide support to employees 24/7. They can also facilitate employees with IT services at an enterprise level and to any department within the organization.

For example, let’s say that one of your employees is having issues with their computer audio and uses a virtual agent to solve this issue. The agent should be able to ask basic questions such as “are you using headphones or your computer speakers?” and then determine what to suggest depending on the response. If the employee says that the headphones are the problem, then the agent could potentially send a request order for new headphones automatically without the employee needing to call the service desk.

While these agents can help reduce the workload of support teams, it is essential for them to also enhance the user experience. Let’s look at how AI helps achieve this.

What is the Relationship Between Virtual Agents and Artificial Intelligence (AI)?

Artificial intelligence has been a hot topic in recent years and AI technologies, which include virtual agents, are on most companies’ wish list.

But even with out-of-the-box solutions, virtual agents still need to be “trained” in order to work properly without sacrificing the user experience. This is where AI capabilities like machine learning (ML) and natural language processing (NLP) come into play. Here is how they work:

  • Machine learning technology focuses on problem solving and allows virtual agents to improve the types of responses and interactions they have.
  • Natural language processing focuses on language analysis, which can help agents better interpret what users are looking for and identify the right knowledge to deliver while improving search results.

But even with ML and NLP, these agents can’t simply predict the information users are looking for, and this is why its success will also depend on where it obtains its information from.

Although not associated with AI, if your knowledge base does not have the right content, then the virtual agent will not be able to analyze it and provide the most accurate information to users’ context. Think about investing in your knowledge base and using a knowledge management tool as part of an ongoing initiative towards improving your user experience.

What’s the Difference Between a Virtual Agent and Chatbot?

This might not be a simple answer. While the terms are sometimes used interchangeably, there is still a debate amongst industry analysts, experts and the technology community on the definition. And it is important to note that although there isn’t one definition everyone can agree on, we can still look at both concepts in terms of their functionality. 

According to Chatbots Magazine, “… a chatbot is a service, powered by rules and sometimes artificial intelligence, that you interact with via a chat interface.” This makes a lot of sense since the word itself is composed of “chat”, which would indicate a conversational or chatter function, and “bot”, which can refer to an application that can be programmed to automate tasks.

On the other side, if we look at “virtual agent”, the composition of words makes it seem that the functions should go beyond “chatter”. Which would also make sense since an “agent” is someone (or something) that can act on a person’s behalf.

However, even though chatbots have been present from decades ago, they have certainly gone beyond a simple chat interface with scripted responses and, like virtual agents, can also benefit from AI technologies like ML and NLP. 

No matter how you define these terms, both technologies should have the capability to identify keywords, access knowledge articles for relevant information, and provide a list of results for the users. But one thing that could help differentiate both concepts is that a virtual agent might go beyond just searching through a knowledge base. The next section shows other capabilities that you should consider.

Things to Consider When Choosing a Virtual Agent

At the end of the day, the purpose of your virtual agent will define how you train it and what capabilities it should have; however, there are some aspects to take into consideration that could be deemed essential.

  1. Omnichannel Access – Users must be able to access agents from anywhere, including mobile apps, messaging platforms, web applications or websites.
  2. Conversational Interface – Natural language processing (NLP) will allow agents to fill in the gaps when users write in less technical terms or use altered terminology, creating consistent conversations and providing a seamless user experience.
  3. Response Accuracy Capabilities – Not only will filling in the gaps help with the conversation flow but with the use of machine learning (ML) the responses can be generated more accurately and relevant for users.
  4. Automation Features It may seem obvious but not all bots can execute user requests automatically without the need for a pre-programmed script—automation features are important because it’s what helps minimize human agent involvement.
  5. Software Integration – Incorporating the agents with ITSM tools, CRM platforms or knowledge management software allows it to exchange information easily between applications and even between departments in your organization.

With the above capabilities, virtual agents can provide customers and employees with a consistent and interactive user experience. Learn more about how you can integrate this advanced AI technology and knowledge management to elevate the user experience in your organization: see a live demo.

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Erika Troconis-Rodell

Erika Troconis-Rodell is the Content Marketing Manager at EasyVista. With 6 years of experience in marketing, she currently focuses on content development, copywriting and the blog strategy for EasyVista. Erika loves all things technology and enjoys reading about ITSM, IoT, and SaaS. Fun fact, she also speaks Spanish, French, and Mandarin.