In the last couple of years, interest in artificial intelligence (AI), chatbots, and machine learning has grown among business leaders looking to optimize company operations and provide better experiences for both customers and employees.
Virtual agents can now be added to that list as organizations pursue new ways to solve problems more efficiently. They want to do more (like offering better experiences and results) with less (like arduous implementation processes and deployment fees).
This potential for improving user experiences while simultaneously cutting costs is the driving force behind the rapid adoption of virtual agents for both customers and employees. This guide explores the use of virtual agent technology, including how it works, its benefits, challenges, and a few real-world examples.
What is a virtual agent?
A virtual agent is, in essence, a bot, or software that simulates human activity via automation without human intervention. Virtual agent bots automate dialog with users, pulling from a pre-defined set of data to answer and perform specific actions for customers.
Virtual agents combine a variety of specific technologies like intelligent search, natural language processing (NLP), and robotic process automation (RPA) into a single user interface most often taking the form of a chatbot for speed and efficiency. These components have been around for years, but combining them into a single solution is a relatively recent development.
How virtual agents work
AI technology built from machine learning (ML) algorithms and advances in natural language processing (NLP) allow virtual agents to respond well to almost any request. Consider how quickly and thoroughly Alexa and Siri can retrieve information from the web, schedule events, and make purchases.
Their NLP capabilities allow them to analyze speech and text with increasing accuracy, demonstrating that this technology can perform a range of complex tasks rather than simple, standardized requests.
Many virtual agents are available, but not all of them excel at this type of analysis. Basic chatbots are still limited in scope, as they only provide basic answers to pre-defined questions. Due to the wide range of capabilities, it’s a good idea to request thorough demonstrations of virtual agents before committing to implementing one as part of your business optimization strategy.
Virtual agents vs. virtual assistant vs. chatbots: what’s the difference?
Virtual agents have some overlap with related technologies like virtual assistants and chatbots; these terms have no rigorous definitions that all AI experts agree on. While these terms are sometimes used interchangeably, consensus exists regarding some of the technological distinctions between the related tools:
Chatbots vs. virtual agents
A chatbot is a general term for any program that simulates a real-time conversation with a human. If they use voice prompts rather than typed ones, they’re known as interactive voice response (IVR) systems.
Chatbots typically use decision trees, or algorithm-generated flow charts, to manage customer interactions. But that doesn’t necessarily require AI, you may by thinking, and you’re right. A chatbot can rely on pre-programmed inputs to trigger a pre-scripted answer with no applied machine learning or RBA technology.
Chatbots don’t have the ability to parse inputs they haven’t been programmed to recognize, so they are only suitable for replying to questions with basic answers, like inquiries about store hours or customer call routing.
In comparison, virtual agents have AI capability that allows them to infer the desired response, even when the input doesn’t exactly match their programming.
Virtual assistants vs. virtual agents
A virtual assistant can refer to either a human being or software that provides remote assistance. When comparing a virtual assistant to a virtual agent, virtual assistant refers to software.
Amazon’s Alexa and Apple’s Siri are the best-known examples virtual assistants. They act as an extension of the user and can automate actions that users frequently perform themselves, like sending a text, ordering an item, playing a song, or dimming the lights.
In comparison, a virtual agent is an extension of a business. It automates actions for customers or employees, like updating log-in credentials or paying a bill. They also include conversational AI that helps determine the user’s intent and the steps needed to meet that intent.
Furthermore, virtual agents can continuously improve their ability to perform these tasks. A virtual agent can understand and learn what the user wants, while a virtual assistant can only respond to pre-defined inputs.
Benefits of virtual agents
You may have inferred from these capabilities and comparisons that virtual agents can be a valuable addition for businesses intent upon streamlining processes and improving customer experiences. Virtual agents have several other big benefits, however. They include:
Virtual agents provide answers to frequently asked questions and common issues. Customers who receive quick, thorough resolutions tend not to care whether that resolution came from a human or a machine. As live agents work to help customers, virtual agents can escalate issues that are beyond the agent’s scope to the appropriate manager.
Streamlining customer interactions reduces the need for a large staff. In addition, virtual agents optimize resource allocation by allowing live agents to focus on complex queries requiring their expertise rather than answer call after call repeating the same answers.
24/7 customer service can be challenging for any business. Customers, meanwhile, have grown to expect it. This capability requires either a sufficient in-house staff or outsourcing to call centers that are often located in another country. A virtual agent is available at all times and has the capability to answer most routine questions.
In cases where the questions are more complex, a virtual agent can schedule a call back from a live agent when business hours resume. This approach may not provide an immediate answer, but it expresses to customers that their issue is a priority.
Faster and more consistent responses
Obtaining a fast answer is one of the most common reasons customers use virtual agents. Studies consistently show that people prefer speed to accuracy in their communications with businesses.
Virtual agents allow customers to instantly begin a conversation and receive possible solutions. What’s more, virtual agents’ ability to request clarification and repeat their understanding of provided information serve as a giant first step toward information accuracy.
Increase employee time for high-value interactions and complex requests
For many teams, time-consuming work like answering simple questions, navigating customers to the appropriate channel, or sharing basic information is a daily blocker to productivity and contributions toward larger company initiatives.
By employing a virtual agent to handle simple requests, employees’ time is freed to use their expertise for strategic initiatives like finding root causes of common customer complaints or initiating one-on-one customer interactions for better relationships.
Virtual agent challenges and limitations
No technology is without shortcomings. In the case of virtual agents and AI, those limitations lay in their human interaction capabilities. Though responsive and thorough, they have yet to break the barrier of natural, seamless communication with humans in a couple of areas:
Limited understanding of context
Virtual agents are sometimes unable to accurately answer questions because they lack the proper context or don’t fully understand the user’s intent. Obtaining an effective resolution from a virtual agent requires it to understand natural language, including slang, complex grammar, common misspellings, and synonyms.
The ability to derive context from the entire conversation is also essential for virtual agents to be effective. An important additional capability of effective virtual agents is that of asking clarifying questions in order to reduce ambiguity.
For this reason, the continued development of a virtual agent that can continuously learn and adapt is key.
Inability to handle emotional complexity
Because virtual agents don’t have emotions, they answer questions mechanically. This tendency can annoy customers who are accustomed to talking to live agents who are sensitive to emotions. The emotional intelligence of most humans allows them to hear issues, understand methods and urgency, and apply humanity and creativity to solve problems; virtual agents simply aren’t capable of this.
Key features of an effective virtual agent
There are currently several options for businesses in search of an effective virtual agent. The final decision will consider your customer support needs, along with those of the teams that provide customer support. In addition to those needs, consider these features, as well:
A virtual agent should improve its performance over time by learning from its own mistakes. For example, a customer becomes confused and frustrated when a virtual agent transfers their call to a live agent because it does not understand the customer’s intent or isn’t able to process it.
This type of transfer can significantly impair customer experience, which is a key factor for remaining competitive in today’s business environment. It can leave a great customer with the impression that they aren’t being clear enough or stating their issue in an easily understood manner. A good virtual agent should reduce the rate of confusion transfers after going live rather than multiply them.
A virtual agent’s greeting and overall response flow sets the tone for the customer interaction, which is key to determining the customer’s overall impression of the exchange. Customers need to feel that a service agent is empathetic, whether it is a chatbot or live agent. Generic, or “canned” greetings and responses make customers doubt the virtual agent’s ability to handle a request, but a personalized message can put them at ease.
Personalization can include actions like including the customer’s name in the greeting, capturing previous requests and making relevant announcements. Virtual agents can also add customized names and logos that add another layer of familiarity, helping to create brand loyalty. Customers should still feel that service representatives are intelligent and caring, even when they know they aren’t humans.
Natural language processing (NLP)
NLP is a crucial feature of virtual agents, as it provides them with the ability to “hear” or “read” spoken or written words. It translates speech and text into machine-readable language, and gives the virtual agent the ability to determine the conversation’s context and the customer’s intent. Once it’s virtually read or heard the text, NLP generates clear content that facilitates human-machine conversations that resonate with the user.
Most businesses use dozens of software solutions, which means it’s vital that virtual agents connect with customers and employees via their current applications.
Many virtual agents can be integrate with mobile apps, web portals, and collaboration tools like Microsoft Teams, Slack, Google Calendar, and request portals.
Integrations make the virtual agent experience efficient by allowing seamless transition from one app or system to another. They work together to provide real-time solutions in processes such as following up with customers, escalating support requests, and scheduling demos or service calls.
3 examples of virtual agents
Virtual agents’ power to surpass simply answering questions makes them useful in many business processes, including procurement, HR, and IT. The following examples show specific applications for virtual agents in these areas.
Procurement is a complex series of activities and workflows used to manage purchase requests, mitigate supplier risk, increase company savings, and keep accounts payable balanced.
Because of the many interwoven processes and people, it’s not uncommon for parties involved to reach out for status updates. For large enterprises managing a high volume of requests, this can be both tedious and time-consuming.
With the help of a virtual agent, procurement teams can create personalized journeys for requesters and suppliers to help answer questions and provide status updates on payments or purchase requests — all without any intervention from procurement.
Enterprises may use virtual agents to manage their internal employee workflows that are common in HR. For example, employees with questions on diverse topics from pay to healthcare can use a virtual agent to handle their questions in real time, rather than requiring HR staff to do it.
This not only saves HR teams time that can be reinvested in more 1:1 conversations with employees, but it also provides employees with a resource that is responsive and readily available whenever they need it.
A company’s IT department often makes the heaviest use of virtual agents, especially for servicing help desk tickets. These support tasks include routing calls, delivering knowledge articles and answering commonly asked questions.
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