A Comprehensive Guide to Virtual Agents

by Jonathan Redsell

Virtual agents, such as chatbots, are transforming how businesses connect with customers and streamline operations. At their best, these digital assistants create seamless experiences, answering questions instantly, processing requests 24/7 and freeing up your human team for more complex interactions. The potential is huge, from boosting customer satisfaction to reducing operational costs.

But let’s be honest, we’ve all encountered bots that left us feeling frustrated rather than helped. The good news? With the right approach, your bot can be one that users genuinely appreciate and maybe even prefer for certain tasks.

1. What is a virtual agent?
2. Virtual agents vs chatbots vs conversational agents
3. Key features of virtual agents
4. Types of virtual agents
5. Virtual agents vs chatbots vs conversational agents
6. Tips for creating a high-value virtual agent
7. How to make a chatbot sound more human
8. How to calculate virtual agent ROI
9. Deploy virtual assistants with Netcall

What is a virtual agent?

A virtual agent is a software application that uses artificial intelligence (AI), natural language processing (NLP) and robotic process automation (RPA) to provide information and respond to user requests. Most commonly, this technology takes the form of a chatbot and responds to user requests in a human-like conversational manner.

Intelligent virtual agents are often used by organisations to support customer services, as they can handle routine questions, assist with simple requests and complete basic tasks. By automating these interactions, businesses can free up human agents to focus on more complex or high-priority issues. This not only helps improve efficiency but can also lead to quicker response times and a better overall customer experience.

Key features of virtual agents

A high-performing virtual agent must possess several core, advanced capabilities beyond simple keyword recognition:

1. AI & Natural Language Processing (NLP): The ability to accurately interpret the intent and meaning behind a user’s unstructured input, even with misspellings, slang, or regional variations.
2. Contextual understanding (Memory): The agent can remember previous turns in the conversation, allowing for natural follow-up questions and maintaining flow, rather than treating every message as a new, isolated query.
3. Integration: The capacity to connect with backend systems (CRM, ERP, knowledge base, ticketing systems) to retrieve personal data, update records, and execute transactions like “Change my address,” or “Check my order status”.
4. Personalisation: They can provide personalised support by using a customer’s history and preferences to customise interactions.
5. Omnichannel deployment: The ability to provide a consistent experience across multiple channels (website chat, mobile app, WhatsApp, SMS, voice bot), ensuring continuity regardless of where the customer starts the interaction.
6. Continuous learning: Utilising analytics and feedback loops to identify knowledge gaps, correct failed interactions, and autonomously improve response accuracy over time.

Types of virtual agents

Virtual agents can be categorised based on their primary channel and function:

The key takeaway is that the most sophisticated solutions today are often hybrid and omnichannel, combining text and voice capabilities to meet the customer where they are. Hybrid virtual agents integrate the functions of rule-based and AI-driven virtual agents. They manage routine questions through established rules and use AI for more complex tasks. Such agents are often employed in contact centres to deliver real-time customer assistance. This includes providing critical support to internal staff, such as using a virtual assistant for insurance agents to drastically reduce administrative load.

An example of an integrated chatbot

Netcall’s virtual agent is a combination of voicebots, IVR, and chatbots with intelligent routing ability, helping your businesses improve efficiency, productivity, and bottom line overall.

Virtual agents vs chatbots vs conversational agents

While these terms are often used interchangeably, there are differences between virtual agents, chatbots and conversational agents in terms of their capabilities.

A chatbot is typically a rules-based tool designed to respond to specific keywords or pre-programmed inputs. If a recognised input is triggered, the chatbot will trigger a scripted response. The nature of chatbots means that they are typically used for straightforward tasks like answering FAQs or responding to simple requests.

A virtual agent, on the other hand, is usually more advanced. It is a software application that uses technologies like AI, NLP and RPA to understand context, manage more complex queries and carry out automated tasks. Unlike chatbots, they are able to continuously improve.

Conversational agents refer to any system designed to engage in a dialogue with users, whether that is through a chatbot or virtual agent.

Tips for creating a high-value virtual agent

Whether you call them virtual agents, virtual assistants or chatbots, these digital helpers are popping up everywhere. The big question is: How do you create one that delivers real value to both your users and your organisation?

1. Define the purpose of having a virtual agent

There’s no magic formula for the perfect intelligent virtual agent, but to get it right, we recommend starting by asking yourself some basic questions before you dive in:

1. What problem is your bot solving?
2. How will it make life better for your customers (and your business)?
3. What are people already contacting you about that a bot could handle?

If your bot isn’t going to make something easier or better, why build it at all?

Use the Value-Irritant Matrix

The Value-Irritant Matrix from Bill Price (Amazon’s former Customer Service VP) can help identify the purpose of your virtual agent. It uses a grid format to highlight 4 use cases:

1. “Please Don’t” – These are things that frustrate both your customers and your business. Don’t automate these headaches – fix the underlying problems first!
2. “Make It Simpler” – Your business needs these processes, but customers find them annoying. Focus on making these interactions smoother rather than just automating the pain.
3. “Human Touch” – These are the golden interactions that both your organisation and your customers value. Keep these with your human agents when possible.
4. “Bot Sweet Spot” – Things customers need but are tedious for your business. This is your automation bullseye! Think balance checks, appointment scheduling, status updates and returns.

Check out the official matrix in our guide, with real data examples: Getting Started With AI Agents.

2. Use your data to your advantage

Before you build anything, look at what your existing data is telling you, from contact centre stats to website behaviour. By analysing your data, you can build a bot that has meaningful interactions with your customers.

It’s important to consider whether you’re interacting with people who might find technology intimidating. Keeping it simple is generally always good advice.

For voice bots, consider: Will regional accents be an issue? Do you need to offer multiple languages?

3. Be realistic with the functionality

This is a big one. Before you promise your bot can change a customer’s address, make sure it can actually:

1. Verify who they are
2. Access their current details
3. Update your systems.

Too many chatbot projects crash and burn because someone promised functionality that the underlying systems couldn’t support. If integration isn’t possible, be honest and direct people to alternatives.

“Let’s talk about generative AI for a second. It’s a game-changer for Q&A bots, letting you handle a much wider range of questions without manually writing hundreds of responses. If you don’t have access to this tech, keep your scope tight and focused on your most common questions.”

Jonathan Redsell

Partner Success Manager, Netcall

4. Test, fix, repeat for the continuous improvement loop

Once your bot is built:

1. Get a diverse group of colleagues to try to break it
2. Make a clear list of the requirements it needs to meet
3. Fix what’s not working and enhance what is
4. Test again (and again).

Remember, your virtual agent is never really “done.” Keep an eye on what questions trip it up and where people abandon ship. Whether those abandonments are good (they got what they needed quickly) or bad (they gave up in frustration).

5. Treat your bot like a team member

When done right, your virtual agent becomes an integral part of your customer service team. Think about it like you would a new employee: Give it a clear job description, train it properly and equip it with the right tools. And don’t forget to review its performance regularly and help it to continually grow its knowledge and skills.

By focusing on solving real problems instead of just implementing flashy tech, your bot will become a valuable team member that both your customers and agents appreciate.

How to make a chatbot sound more human

One trick for making a chatbot sound more human is through role-play!

Get two people in a room: one plays the customer trying to complete a specific task, the other plays the bot, limited to what the bot actually knows and can do.

For chatbots, use Teams or WhatsApp to simulate the experience. For voice bots, do it over the phone or sit back-to-back (no cheating with visual cues!).

Try this with different “types” of customers, including people who don’t know your business well. You’ll be amazed at how many edge cases and natural conversation flows you’ll discover.

How to calculate virtual agent ROI

To compete with industry leaders, you must focus on the financial benefits. Deploying AI virtual agent delivers measurable ROI across three key areas:

1. Cost reduction: Automating Level 1 and Level 2 support requests reduces reliance on human agents, lowering staffing and overhead costs. Track the Average Handle Time (AHT) and Cost Per Contact (CPC) before and after implementation.
2. Revenue generation: 24/7 availability captures sales opportunities outside business hours and enables automated upselling/cross-selling through embedded features in the bot’s workflow.
3. Efficiency & scale: Human agents are freed up to focus on complex problem-solving, high-priority accounts, and value-added tasks, leading to better employee satisfaction and quicker issue resolution.

Deploy virtual assistants with Netcall

At Netcall, we help organisations transform their customer service through intelligent conversational AI and chatbots. With Liberty Converse, your customers get instant answers to routine queries, while your contact teams can focus on complex, high-value interactions.

Ready to enhance your customer experience?

Get in touch with our team to see how our virtual agent solution, Liberty Converse, can support your service goals and streamline your operations.

About the author

Jonathan Redsell

Partner Success Manager

Jonathan brings 20+ years of hands-on experience to the forefront of customer journey transformation. He specialises in growing and modernising contact centres, precisely pinpointing areas for improvement to facilitate effective multichannel communication. Holding qualifications in conversational design, Jonathan adeptly bridges the gap between human requirements and AI functionality. Jonathan is committed to helping businesses enhance customer interactions by thoroughly considering the needs of both the individual customer and the AI system, ultimately driving improved operational efficiency and customer satisfaction.