What are Chatbots & How are They Different from IVR and Virtual Agents?

The rapid evolution of AI has generated an adoption boom of automation and RPA by contact centers. The three main capabilities are chatbots, conversational IVR, and virtual agents, with diverse use cases spanning everything from customer service management, payment processing, and generating and qualifying leads. 

But what’s the difference between them? And how do you know whether one, or all three, are right for you? We sort through the confusion below. 

Chatbots vs. IVR vs. Virtual Agents: What’s the Difference?


At their most fundamental level, chatbots are AI-driven computer programs that simulate human conversation and allow interactions with digital devices to unfold as if chatting with a real person. A chatbot can be a catch-all term that describes any automated voice or digital interaction. Chatbots rely on rule-based configuration, which means they require human input to evolve and change. For instance, a chatbot won’t automatically know when a new knowledge base FAQ article can answer a customer query—you have to tell it to surface that information.

Conversational IVR

Advanced IVRs take the legacy IVR touch-tone input one step further by comprehending the caller’s speech, albeit within the scope of understanding defined by programmed keywords. Conversational IVRs layer in natural language processing (NLP) to parse and interpret indirect phrases, incomplete sentences, and even context. Because they use AI and machine learning, conversational IVRs are capable of improving proficiency over time. 

Virtual agents 

Similar to conversational IVR, virtual agents have the additional layer of natural language processing. Where chatbots rely on the programmed knowledge base and conversational IVRs rely on voice inputs, virtual agents do both by pulling from that base as well as the custom NLP algorithms that “train” it to speak and sound more human-like.

How are they different? 

Chatbots, IVR, and virtual agents are all points on the automation spectrum. 

When deployed, they help customer service teams more effectively route issues and provide customers quick self-service opportunities. 

They differ in several ways, though they achieve many similar outcomes with distinctions that add important functional nuance to the use cases they satisfy.

Broadly speaking: 

  • Chatbots don’t use AI in tandem with machine learning to “learn” 
  • Chatbots also don’t use speech recognition and are usually incapable of handling complex communication unless otherwise programmed.

How are they similar?

All three are task-oriented

Chatbots are rule-based, using an “if, then” system to make decisions about what comes next in the conversations with your customers. Their functionality is limited by known variables as little machine learning is integrated. 

Task-oriented conversational IVRs and virtual agents use natural language processing to provide automated responses to inquiries. 

All three are data-driven

Omnichannel web chatbots are rule-based, while the more advanced IVR and virtual bots use machine learning to improve interactions. Both rely heavily on customer data, they just tap into it in different ways. 

All three can record, associate, and infer sets of data from conversations with your customer. When your customer asks for account information, AI-powered chatbots can learn from past interactions that said customer wants information about account 123456789. They use AI to build personalization into the conversation based on profiles and past behavior. In this way, AI-driven chatbots are better able to anticipate your customer’s needs and provide accurate recommendations. 

While task-oriented chatbots accomplish mundane tasks easily and efficiently, data-rich intelligent AI bots ice the customer service cake. 

They all offer a wide scope of ability

The scope of what chatbots, IVR, and virtual agents can accomplish is quickly broadening. Many can help customers modify account information, make payments, or ask technical questions about a product. NLP allows those requests to be conversational and specific. By leveraging AI, chatbots can hone their ability to serve your customers. 

Take, for example, the task of figuring out what ink to buy for your printer. Imagine a chatbot that could answer that question, plus offer a way to purchase replacement cartridges. 

With machine learning and the ever-expanding internet of things (IoT), this same chatbot could potentially send out a reminder to your customer the next time their ink is running low paired with the option to purchase the right type of cartridge all from the same interface. Now that’s customer service.

They all offer always-on service with instantaneous answers 

70% of customers say they expect an immediate response time when they submit a complaint. Wow! You can keep your customers happy simply by immediately responding to their complaints. Easier said than done, right? With inbound call volume at an all-time high, giving an immediate response seems more difficult than ever. 

Chatbots, IVR, and virtual agents never sleep. This means your customers can contact you 24 hours a day, seven days a week. Integrating a chatbot into your customer support plan gives your customers more options when it comes to the time of day they can contact you. The wider those options are, the happier your customers will be. 

Chatbots, conversational IVR, and virtual agents can lend a hand here, too. When customers are met with a conversational IVR or virtual agent, the AI on the other end can be programmed to handle complaints and direct them to a resolution. 

To best resolve a complaint, human agents are sometimes necessary. But bots can front load information intake, making sure your customer feels heard and your agent is prepared going into the conversation with all the right details—saving critical time and limiting frustration

They all enhance self-service & refine customer journeys

Making yourself available on whatever channel your customer chooses is no longer optional. Customers increasingly expect to be able to reach out across messaging platforms. Be it Slack, Facebook Messenger or WeChat, customers want to talk to you on the channel of their choice and those channels are usually digital. With the increasing popularity of Alexa and Google Home, people have grown accustomed to smooth speech recognition and demand that same ease when they call you for help. 

The tasks accomplished over messaging apps and IVRs don’t need to be complicated. Using task-oriented chatbots and intuitive virtual agents, customers can get quick responses to their queries without the headache. 

They all help create personalized experiences

A personalized customer experience signifies that you take your customer’s interests to heart. What’s more, tailored conversations can get right down to what they need. Chatbots that leverage AI create personalized customer experiences by building on past conversations, and a personalized experience translates to better customer engagement. 

AI-driven bots, conversational IVR, and virtual agents are a logical solution for a contact center that makes customer experience a top priority.

Expect to see AI bots become more and more commonplace. Considering their practicality, how could they not?

Should you use one or all of them? 

As you can see by now, each capability offers distinct benefits, it just depends on your use case. 

In short, chatbots can answer straightforward questions and process simple tasks. They also require a knowledge base. 

Conversational IVR and virtual agents, with the help of AI, can address the core demands of customers, understand verbal nuance, engage in a human-like manner, and get smarter with every interaction.

Quality inbound customer service ensures the amount of time your customer spends getting to a resolution is brief but thorough, anticipates needs, and answers inquiries completely. 

Chatbots, conversational IVR, and virtual agents check all of these boxes.

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