5 Ways Intelligent Virtual Assistants Have an Edge Over Chatbots


This is PART TWO of a series of articles on Intelligent Virtual Assistants. You can also read about PART ONE and PART THREE.

The terms chatbot and Intelligent Virtual Assistant (IVA) have often been used interchangeably by customers and businesses alike, to refer to conversational interfaces that respond to a user’s inputs. And while the core concept between chatbots and IVAs is essentially the same, there is a substantial difference between them in terms of scope, complexity and capability – all of which are far greater in IVAs.

To put it simply, IVAs are the culmination of a decades-long evolution of chatbots.

A chatbot is an automated or pre-programmed conversational interface that can be used to execute basic tasks – such as responding to routine customer queries, dispensing information, collecting customer details etc. 

IVAs are the product of advancements in Machine Learning (ML) and Natural Language Understanding (NLU) that have significantly enhanced the capabilities of chatbots – making them far more intelligent, adaptable, and capable of serving customers in a more comprehensive manner rather than rigidly focused on a limited number of tasks. 

Rather than simply performing routine tasks based on specific inputs, an IVA truly serves as an ‘assistant’ for a customer – emulating human interaction while carrying out a wide variety of tasks to help customers. 

We delved deeper into the evolution of chatbots into IVAs, and the fundamental differences between the two in our previous article. For a quick overview of the key differences between chatbots and IVAs, take a look at the table below:


Let us now take a closer look at some of the specific capabilities that give Intelligent Virtual Assistants a clear edge over chatbots!

1. IVAs Can Understand Customers Better

Chatbots have a limited ability to understand a customer’s requirements, specifically with regards to complex queries. This is because they lack a strong foundation in Natural Language Understanding (NLU). They are limited by structured dialogue – only able to respond to questions or inputs for which they have pre-programmed responses. 

Even chatbots that do possess some NLU capabilities rely on open-source libraries that are not customized to a brand’s industry or customers. As a result they are unable to understand the intricacies of written or spoken human conversation.


Contrast this with Intelligent Virtual Assistants, which have robust NLU capabilities that enable them to understand ‘natural’ and free-flowing human conversation, including slang, and respond appropriately – thus providing customers with a more interactive experience.

Moreover, IVAs can make use of custom NLU models that are specific to a particular brand or industry vertical. This significantly enhances their ability to accurately determine a customers’ intent. IVAs utilize artificial neural networks, which allow them to learn from new situations, constantly expand their scope of tasks and enhance the quality of interaction they’re capable of. 

Last, but not least, IVAs can be equipped with the ability to understand and respond in multiple languages, as well as handle the use of ‘mixed languages’ by a customer.

Essentially, IVAs are far more effective than chatbots when it comes to simulating the experience of a conversation with a helpful and knowledgeable human agent.

Learn how a Multilingual chatbot can give wings to the CX transformation initiative and improve overall ROI for your business

2. IVAs Can Understand and Retain Context

A chatbot’s reliance on structured dialog significantly impedes its ability to understand and maintain context. The bot follows a rigid conversational flow, and when it is unable to understand the customer’s intent, the flow breaks. Chatbots are also often unable to retain context over the course of a conversation, or between two different conversations with the same user. 

Intelligent Virtual Assistants, on the other hand, work with dynamic dialog i.e. they are not bound by a rigid conversational flow, and can extract contextual data from a customer’s conversation, irrespective of the order in which it is given. 


An IVA can retain context across multiple conversations, thus contributing to increased customer convenience, as seen in the example above.

Moreover, an IVA not only retains context throughout a single conversation but can only retain it between two different conversations. It offers a seamless experience to the customer across multiple engagements with the brand, while also maintaining high levels of automation and accuracy.

3. IVAs Can Perform a Wider Range of Tasks

Given their limitations when it comes to understanding customer intent and maintaining context, chatbots can only perform basic, routine and repetitive tasks – such as responding to FAQs or form-filling. 


Intelligent Virtual Assistants, on the other hand, can perform a much wider range of tasks. For instance, an IVA can understand a customer’s requirements and assist them with product discovery. It can make recommendations based on customer’s stated requirements or past behavior, or help the customer compare multiple products. It can provide customers with information or advice about a brand’s products or services. It can seamlessly resolve simple customer queries or escalate a complex query to a live agent where appropriate, even without explicit prompting by the customer.

4. IVAs Facilitate Seamless Voice-Driven Experiences

When it comes to conversational experiences, brands are increasingly becoming voice-first. A report by Juniper Research predicts that there will be 8 billion digital voice assistants in use by 2023! 


Unlike traditional voice chatbots, which rely on pre-recorded responses triggered by specific user inputs, voice-based Intelligent Virtual Assistants use their deep domain knowledge to create a truly seamless voice experience. They recognize the customer’s intent from their free-form speech, and respond to the customer naturally using the appropriate tone and language. 

This characteristic of IVAs is particularly useful when it comes to facilitating conversational commerce – effectively simulating the experience of talking to a sales assistant to understand and compare product features, enquire about pricing, make purchases etc.

Interactive Voice Response (IVR) is a voice-driven conversational interface that has been significantly enhanced by evolving to the IVA stage. Unlike traditional IVR, which forced a customer to navigate a complex menu and offered a limited number of tasks, Conversational IVR can pinpoint a caller’s intent and execute the most appropriate task to resolve the customer issue. The IVR system’s ML capabilities also enable it to learn over time and gain the ability to respond to increasingly more complex and varied query types – significantly transforming the brand’s customer care.

5. IVAs Are Customer Oriented

While they are deployed to provide customer care, chatbots are ultimately server or company-oriented. They literally force the customer to follow the company script – which will not necessarily lead to optimal outcomes for the customer or for the brand. They offer the customer a limited number of tasks, which may or may not match the customers’ intent.

Intelligent Virtual Assistants, on the other hand, have the ability to be customer-focused. They are flexible enough to allow customers to communicate their intent in their own words. They can communicate with customers in the language of their choice. They allow customers to access information, services or tasks at their own convenience, rather than forcing them to follow a cumbersome pre-defined flow. 

To truly live up to its name as an Intelligent Virtual ‘Assistant’, an IVA needs to be able to do everything that a customer service agent or sales assistant can!

This simple example, illustrated in the example below, demonstrates the vastly superior scope and quality of customer service and engagement that an IVA can provide, as compared to a chatbot.

chatbot vs iva

A chatbot (pictured left) and an IVA (pictured right) deal with the same customer query very differently.

Consider a simple customer query – “I am unable to access my account”.

A chatbot might, at most, pick up the keywords “access” and “account” and share information that might help the customer access their account. 

An IVA, owing to its ML capabilities, will be aware on the basis of past data that when a customer says “I am unable to access my account” it usually means that they need their password to be reset. The IVA would then immediately offer the customer the option of resetting their password using a security question or e-mail ID/phone number. An advanced enough IVA might even be able to complete the password reset itself, and then simply inform the customer of the task completion!

To sum up…

So you now know precisely how Intelligent Virtual Assistants can leverage their advanced ML and NLU capabilities to truly be ‘intelligent’ in their interactions with customers. They can converse with customers in a seamless and natural manner, understand precisely what they want, and take decisions to execute the tasks that will fulfil those specific requirements end-to-end.

The swiftness, convenience and personalized service that IVAs offer will certainly appeal to customers, in turn boosting their engagement with your brand. This ultimately translates into more conversions, more sales, and a quantifiable positive impact on your businesses’ bottom line!


Are you interested in developing an Intelligent Virtual Assistant solution for your brand?


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