Conversational Intelligence vs. Chatbots: Everything You Need to Know

Brands are constantly looking to drive down costs and accelerate response times for customer queries. In fact, by 2022, an estimated 88% of online users had experienced at least one interaction that was handled without human involvement.

Artificial intelligence (AI) companies have been quick to respond. Now, chatbot systems have been designed to offer a more “real life” experience: Conversational AI. But what is this technology? And how is it different from a regular chatbot?

This article offers a 101 guide to all you need to know about chatbots and conversational AI. We break down why so many businesses are starting to implement automated digital messaging and quickly move the needle on CSAT.

At its most basic level, a chatbot is a messaging system that allows website visitors to interact with a brand using their device. Typically chatbots use a text-based approach, either through messaging pop-ups or a website-integrated chat interface. This allows the user to hold semi-intelligent “chats” with quick answers to common queries.

When we talk about “traditional chatbotting,” we’re referring to a rule-based bot: A system programmed with a preset workflow built around pre-written questions and answers. In layman’s terms, rule-based chatbot “chats” exist long before an inquiry is made. The visitor triggers a conversation through pre-written questions, before the chatbot guides them through a mapped-out, FAQ-style conversation flow — with no ability to deviate.

Their ease of use, quick setup and affordable deployment have seen rule-based chatbots become one of the most popular brand contact channels the world over. In fact, their use increased by a staggering 92% between 2019 and 2020.

The traditional customer service landscape can be noisy and chaotic, and greatly impractical for the user. Slow responses, long customer wait times and untrained support agents can be seriously detrimental to a brand’s reputation.

In fact:

According to Comm100, chatbots handle nearly 70% of customer-led chats from start to finish. From an operational stance, this is a win-win. Chatbots can (and, in many circumstances, have) reduced the reliance on physical customer support staff answering calls or responding to customers. In theory, the customer’s query is resolved faster and thus the average cost-per-customer-interaction is driven down.

Conversational AI is an emerging field at the intersection of artificial intelligence (AI) and natural language processing. Its purpose is to create interfaces that can understand context and respond to natural language inputs empathetically and meaningfully — just as a human would.

The technology may seem a world away from the rudimentary, rule-based chatbot, but it’s actually more similar than you might expect. Think: ChatGPT, Google Bard, Siri, Amazon Alexa. These are all examples of conversational intelligence that enable more intuitive, fluid and natural interactions with machines, making technology feel more personalized and accessible.

This implemented AI takes chatbotting to a whole new dimension, no longer constraining the user to simple pre-defined FAQ responses, but opening the door to all manner of complex customer queries. It’s been used to cancel memberships, close accounts, upgrade plans and more — all without any human intervention.

Conversational AI chatbots work by blending natural language processing (NLP) and machine learning (ML) to understand and respond to user inputs in a meaningful and conversational manner. Here’s a simple overview of how they typically work:

The chatbot begins by employing NLU to extract meaning from the user’s input. NLU involves tasks such as intent recognition (identifying the user’s purpose or request) and entity extraction (identifying relevant context like names, dates, or locations).

After identifying the user’s intent, the chatbot utilizes dialog management to determine the appropriate response. It considers conversation history, customer data and pre-defined workflows to provide the most meaningful interaction possible.

Depending on the chatbot’s purpose, it may be powered by a knowledge base or customer help center. The chatbot can intelligently scour these resources to find the right information and provide accurate responses to user queries.

Once the chatbot has gathered necessary information, it utilizes natural language generation software processing to generate a response in an authentic, human way. NLG involves transforming structured data or system outputs into easily understood, contextually appropriate language in the user’s native tongue.

Machine learning allows the chatbot to improve performance over time. It can learn from user interactions and feedback to enhance intent understanding, refine responses, and adapt to user preferences to improve the overall conversational experience.

Conversational AI can be armed with customer account data to simulate the human experience and personalized delivery seen in traditional customer service. While not a like-for-like swap, conversational AI can enable companies to retain a sense of brand personality and voice.

Use of conversational AI reduces the reliance on expensive customer service resources — even further than traditional chatbots. With accurate information, smart delivery and native translations, businesses are able to resolve customer queries automatically, freeing up time to invest in more complex areas of their business.

Website visitors want information — and they want it fast. Conversational AI helps businesses respond to emerging customer needs as they happen, keeping customers heard, engaged and satisfied at a much lower cost than agent response. This results in better site navigation, user resourcefulness and overall brand experience.

Unlike a traditional customer service team, a conversational AI chatbot supplies constant, personalized brand interactions around the clock. It provides a consistent information resource, making it less likely that prospects will be deterred by slow responses, and do business elsewhere.

Conversational AI creates an easy and cost-effective way for customers to talk to a business directly. These conversations with customers will, in turn, supply accessible, detailed and actionable data on customer pain points, issues with products, and competitor weaknesses.

Conversational AI is a leap forward that doesn’t just fill the gap where the rules-based chatbot falls short: It takes the system to a whole new level of responsiveness.

While both share the objective of automating conversations, their underlying technologies, capabilities, and scope of application set them apart. Chatbots are suitable for simple, rule-based tasks, while conversational AI systems excel in complex and dynamic conversational scenarios, adapting to user needs and evolving contexts.

As we know, a rule-based chatbot is a bounded system with predefined categories. It’s useful for solving “problem A,” “problem B” and “problem C” — but not necessarily “problem Z.” Long term, conversational AI is designed to bridge this gap, powering the chatbot to deal with human inconsistency. It offers a better understanding of audience intent, and reacts quickly when the user has an unexpected problem or changes their request.

So, conversational AI vs. rule-based chatbots: Which should you use? In the long term, conversational AI is almost always the better choice for a business. It totally revamps the landscape for automated customer service, though not without its own drawbacks.

The cognitive nature of conversational AI in its machine learning and natural language processes make it a time-consuming system to get right.

But, even with the time demands, the unparalleled benefits on offer can make conversational AI a worthy expenditure for any business. Once set up, it can reduce the reliance on human resources, reducing costs across the board by handling everyday tasks with ease.

No matter which system you choose, it’s never worth writing a rule-based chatbot out of the question. Don’t leave your prospects without a constant information resource. Intelligent or not, chatbots are an assured way of boosting user experience and accessibility.