What is an Intelligent Virtual Agent? 5 Key Features You Should Know
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Table of Contents
Introduction
With customer expectations changing and developing all the time, many businesses struggle to cost-effectively scale their customer support solutions or provide responsive and intelligent support when customers need it. Intelligent Virtual Agents (IVAs) are AI-enabled tools that provide new methods of engaging customers across various channels. In this article, we’re taking a closer look at IVAs: what they are, their essential features, and what the future of intelligent virtual agents looks like. Let’s dive in.
Key Takeaways
- Intelligent Virtual Agents are advanced than traditional chatbots: By combining natural language processing (NLP), predictive analytics, and generative AI, IVAs are able to offer contextually aware, human-like support.
- IVAs boost efficiency and reduce costs: IVAs automate basic customer support tasks, enhancing overall efficiency and freeing up human agents to spend that valuable time, money, and energy on more complex tasks.
- IVAs are data-rich: IVAs provide valuable insights into customer behavior and trends, offering businesses more actionable data for informed decision-making.
Defining intelligent virtual agents
An Intelligent Virtual Agent, or “IVA,” is an AI-based software program that emulates human conversations to interface with customers while performing complex customer service tasks. IVAs are more sophisticated than traditional chatbots, using AI, machine learning, and natural language processing (NLP) to form meaningful and helpful responses. IVA responses are more aware of the context of a customer interaction, providing responses that are relevant, personalized, and helpful.
What sets them apart from traditional chatbots
Traditional chatbots are programmed to respond to customers with pre-scripted answers based on certain combinations of keywords. Even if these bots are fairly useful for simpler tasks and customer inquiries, they often have a harder time when it comes to more nuanced conversations, and fail to adapt their approach as the conversation evolves and develops.
In contrast, IVAs are built for dynamic conversations, learning from each interaction, and taking into account the context and emotion behind what is being said. This allows an IVA to generate a real-time intelligent answer that supports customers through complex issues and feels more like a human interaction.
Key features of intelligent virtual agents
IVAs represent a seamless integration of several different technologies. Their most important components are:
1. AI chatbot integration
IVAs can be integrated with chatbots to allow customers the option of automated live chat support, augmented with contextual awareness and the ability to carry out real tasks on the customer’s behalf.
2. Natural Language Processing (NLP) capabilities
Through NLP, IVAs are able to understand more than just the content of a conversation, but also the emotions and intentions behind the words. That gives IVRs the ability to process slang, typos, and variations in sentence structure, and even pick up on sarcasm through tone and word choice.
3. Predictive analytics for enhanced customer interaction
IVAs use predictive analytics to analyze customer behavior and historical data, allowing them to more easily anticipate needs and provide support proactively, initiating outreach before the customer asks.
4. Conversational AI for human-like engagement
Conversational AI is what gives IVAs the ability to maintain fluid, natural conversations. More robotic and formulaic virtual agent tools tend to frustrate customers, damaging the overall customer experience, which makes an intuitive, human-like conversation an essential ingredient for keeping customers engaged in the experience.
5. Intelligent automation in customer experience management
Far from being mere chat tools, IVAs can achieve real results for the customers that interact with them. Integrating into back-end systems, an IVA can carry out simple support tasks like order tracking, appointment scheduling, updates to customer accounts, and more. This not only provides actual support to customers, but also improves the efficiency of human agents by taking more basic tasks off their plates.
How do intelligent virtual assistants work?
IVAs work by combining a variety of advanced technologies into one robust customer engagement tool. Here’s how each component of an IVA works together to provide adaptive, customized experiences to each customer.
Adaptive learning with predictive AI
Predictive AI allows IVAs to recognize important patterns in customer behavior, as well as the context of these patterns. Additionally, predictive AI learns more about the customer’s needs and behaviors from each interaction, building a more accurate picture of how to best assist that customer in the future, tailoring responses to the individual to provide the best experience.
Natural language processing (NLP)
NLP is instrumental in allowing IVAs to understand inputs from customers regardless of how the input is structured. NLP can process not only what is being said, but how it’s being said, developing a clearer picture of customer intention. Key entities, such as product names, dates, and other important data, can be extracted for greater clarity, and new information can be contextualized by information from earlier in the conversation.
The use of generative AI
Generative AI enables IVAs to generate dynamic responses to customers in real-time conversations, accounting for context and individual patient needs. This makes conversations with IVAs more natural and flowing, while still providing the best, most relevant information and support for each customer interaction.
Benefits of leveraging intelligent virtual agents
Intelligent virtual agents have a variety of advantages, including enhancing customer experience, reducing costs, increasing efficiency, and scaling customer support.
Enhance customer experience with 24/7 availability
Through IVAs, customers can receive customized support around the clock, with consistently high-quality service that adapts to their needs.
Reduce operational costs without sacrificing service quality
With more basic tasks covered by IVAs, human agents have their time and energy freed up to tackle more complex customer support issues, giving them the attention they need. With less need to cover every customer interaction with a human agent, IVAs make it more feasible for a small team to cover more calls, saving on operational costs without lowering the quality of the customer experience.
Increase efficiency through seamless automation of routine tasks
Not every customer interaction needs to tie up a human agent. Simpler tasks, like answering FAQs and checking order statuses, can easily be automated, reducing backlogs and allowing each human agent to more on their precious time and energy.
Scale customer support rapidly during high-demand periods
Whether you need to handle a seasonal or promotional demand spike or you’re hoping to scale your operations permanently, IVAs are easily scalable, managing as many conversations as you need without the need to spend more on staffing.
Gain actionable insights from AI-powered analytics and interactions
With every interaction, new data is being created and analyzed. IVAs are able to dive deep, uncovering trends and common pain points, allowing companies to make more informed decisions about business strategy.
Future trends in intelligent virtual agent technology
AI technology is always evolving, and with it, IVAs show a lot of potential for growth in the future. As time marches forward, virtual assistants will likely be able to handle advanced tasks more easily and seamlessly provide more natural and human-like conversation.
Though automated IVA technology will likely gain more proficiency in a greater variety of tasks, there will always be a need for human agents, with the complexities and nuances of human communication. Most customers tend to want to speak to a human agent when dealing with a complicated issue. However, the relationship between human agents and AI technology like IVAs is likely to evolve, with various forms of AI tech becoming trusted tools in a human agent’s tool belt.
Conclusion
Far from just shiny new tools, IVAs have quickly evolved into practical and scalable solutions for meeting — and exceeding — customer expectations. With the seamless integration of natural language processing, predictive analytics, and conversational AI, IVAs go beyond what traditional chatbots can provide, offering customer support tailored to the individual and their specific needs.
