May 13, 2020
Conversational AI

Understanding the key differences between chatbots and virtual agents

By: Henry Iversen, CCO & co-founder, boost.ai. Originally published on Customer Think, 16 Januray 2020

The differences between a virtual agent and a chatbot are actually bigger than you might think. To distinguish between them, we can easily draw parallels to another popular technology.

When it comes to differentiating between chatbots and virtual agents, there is a simple way to get people to separate the two. To see the difference, you only need to draw a parallel to a technology that evolved so drastically from what it used to be that people now use a different term when they refer to it: the smartphone.

Fewer and fewer people regularly use the words ‘telephone’ and ‘smartphone’ interchangeably anymore, primarily because they technically and functionally refer to two very different devices. Yes, both devices can be used to make calls (and a mobile phone can even send text messages), but that’s about where the similarities stop. The modern-day smartphone has a wealth of extra functionality, like continuous access to the internet, countless useful apps and powerful cameras, that make it an essential part of modern life.

So, how is the mobile phone vs. smartphone example applicable to chatbots and virtual agents? While it’s not a complete one-to-one distinction (virtual agents and chatbots are not physical products, after all), the easiest way discern between the two is to ask: what can they do, and how much do they really understand?

The first chatbots saw the light of day in the ‘60s, which makes them older even than the world’s first mobile phone (the Motorola DynaTAC 800x launched in 1983). Even though these chatbots have been improved upon over the years they are still built with simple, rule-based technology, leaving them limited to matching the questions they receive with the most probable, pre-defined answers. This limitation does not make them well-suited to represent an organization or business with high volumes of customer service chat traffic since the human language is too complex and nuanced to be narrowed down to a predefined selection of questions and answers.

A virtual agent, on the other hand, is not powered by the same rule-based programming. Instead, these advanced customer service tools are built with conversational AI at their core, designed to both accurately mimic human conversations and understand the underlying context, content and intent of a customers’ request.

To achieve this, it’s crucial that the conversational AI has a robust natural language understanding (NLU) foundation that combines deep learning and machine learning models with foolproof natural language processing. It’s technical, for sure, but then you should expect no less from a technology that can understand and respond to any input, in any language, while continually improving itself with every interaction.

Virtual agents to go beyond simply answering questions into offering guidance towards products and services and performing a range of complex transactional actions on behalf of users. In addition to providing richer information and handling transactions, a virtual agent can also analyze, advise, sell and up-sell based on customer data - even connecting with other virtual agents other across a network for a truly next-level customer experience.

Chatbots, like mobile phones, just can’t be expected to keep up with this kind of technological advancement.

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