Chatbots Vs Conversational AI: What’s The Difference

According to a recent survey, 70% of consumers would like their virtual assistants to understand them better. They’ve come to expect a more natural conversation with virtual agents so that their customer experience is flawless and the interactions are human-like. 

Today, we’ll discuss the similarities and differences between traditional chatbots and conversational AI-based virtual agents. But first, let’s define the terms.

Chatbots and conversational AI

A chatbot is a tool programmed to respond to a specified range of user’s requests in a predefined way. In other words, chatbots interact with customers based on frequent conversation scenarios that are determined at the stage of development.

Conversational AI is a sophisticated intellectual system (virtual assistant) capable of engaging in a full-fledged dialog with the customers, which involves recognizing the customer’s intent in whatever specific form it comes, asking clarifying questions if needed, and providing the customer with the appropriate service or response.

As you can see, both chatbots and virtual agents are designed to communicate with users and solve their issues in the course of a dialog. However, this is where the similarities end.

Predefined vs Context-based interaction

Most chatbots are rule-based which means they compare user queries against a list of predetermined options and, if it’s on the list, provide the user with the corresponding response. This can work well for some basic FAQs or guiding through a simple process. 

However, chatbots have lots of limitations: for example, they can easily get confused when approached with a non-typical request, or a typical request formulated in a different way. Chatbots are also not aware of the previous context of the conversation – so they can only deal with the current request. 

Unlike chatbots with a predefined communicational structure, conversational AI-based virtual agents rely on a whole bunch of technologies such as Natural Language Processing, Machine Learning, and Predictive Analytics to provide a more engaged and positive customer experience. AI-powered virtual agents are capable of holding meaningful conversations and acting differently depending on the context. 

Because they are constantly learning from each conversation, the quality of communication improves over time. Besides, they are not only trained to discern the user’s intent but also take into account the tone of the message or the user’s emotions, and react correspondingly. Also, intelligent voice agents keep track of the conversation history across multiple channels. This means the AI can recover important information and use it to solve the customer’s inquiry no matter what communication channel was used to start the conversation.

Text-only vs Omnichannel conversations

Chatbots can only interact with users through text, which means they only comprehend text commands or using multiple-choice buttons. Most likely, if you have a chatbot widget on your website and another chatbot in your corporate messenger, they are completely separate and will not recognize the user if they decide to switch between them. 

Conversational AI is more flexible when it comes to different channels of communication. In fact, you can add as many mediums as you wish, including voice-based ones, which makes the customer experience truly omnichannel. For example, one AI-powered virtual agent can simultaneously handle requests coming by phone, via email, messengers, and website widget. 

Besides, when communicating with clients through different channels, conversational AI identifies and ‘recognizes’ them and therefore there’s no need for the customer to explain their issue all over again. This is possible because the information from all the channels is stored in one shared hub. 

Inbound vs Bidirectional communication

Chatbots are designed specifically to handle incoming users’ requests. For example, the most common types of chatbots are website widgets and messenger bots that are programmed to respond to a certain range of questions or requests. Some messenger bots can also send notifications or updates to their subscribers. However, when it comes to full-fledged outreach campaigns, chatbots’ functionality is rather limited.

Conversational AI can be used for both inbound and outbound communications via different marketing channels. Along with responding to users’ requests, AI-powered virtual agents can ring up multiple subscribers, for example, to convey a poll, conduct an HR screening or inform clients about current special offers. What’s more, each of these interactions can be personified and powered by the data from the company’s CRM system, which makes it a perfect marketing tool.

Final thoughts

Despite the enormous popularity of chatbots which are viewed as a simple and affordable solution, their overall efficiency is far from that of conversational AI virtual assistants. If companies are to provide a truly seamless and engaging experience to their customers, they should probably consider adopting a conversational AI platform that can hold human-like interactions via any channel and in any language.

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