Conversational AI vs. Chatbots—What’s the Difference?

What is a chatbot?

A: A sophisticated artificial intelligence interface that engages customers in human-like conversation.

or

B: A glorified FAQ that recites canned answers to a limited set of questions.

If your answer is A, you’re right. If your answer is B, you’re right. And if both answers are right, something’s wrong, because the wide variation in IQ among bots has created a confusing marketplace for conversational solutions.

What (Really) Is a Chatbot?

Up until now, the business world has used the word “chatbot” to describe a range of technology—both new and outdated—that automates customer interactions. Five to 15 years ago, when businesses first purchased the platforms to greet customers who contacted their customer service, the technology was called a “chatbot.” Now, businesses are introducing conversational AI that assists customers with unprecedented efficiency—also sometimes called a “chatbot.”

Confused by broad terminology, some businesses might write off conversational AI as just another bot. But conversational AI goes beyond bots—it will become a new standard for customer experience.

By 2021, Gartner predicts 15 percent of all the world’s customer interactions will be completely handled by AI—a 400 percent increase from 2017. Forty percent of the bot applications companies launched in 2018 will be abandoned by 2020.

Yesterday’s chatbots won’t satisfy customers’ growing demand for personalized experiences. But conversational AI will.

What Is Conversational AI?

Conversational AI is technology that lets people communicate with applications, websites or devices in everyday language. It uses natural language processing to arrange the user’s voice or text input into words and sentences, which it analyzes. The AI then generates the best response based on the data available to it (these responses could be voice, text or performing an action).

But conversational AI’s capabilities go far beyond natural language, especially if we’re comparing them to the standard-issue chatbots—“dumb bots”—that frustrate customers.

Natural language processing

Conversational AI: YES        Dumb Bot: YES

Most chatbots also use natural language processing, but they rely on algorithms and linguistic rules to derive the meaning of a question and choose an appropriate response. The bots become unhelpful when customers ask a question they aren’t scripted to answer.

While conversational AI employs linguistic rules, it also leverages machine learning and contextual awareness (explained below) to create responses. AI does more than correctly interpret a user’s request: it personalizes answers and anticipates needs.

Contextual awareness

Conversational AI: YES     Dumb Bot: NO

Most chatbots don’t know much about the customer beyond what the customer tells them during the interaction. The customer has to speak or key in information that the business likely already has, like account numbers, every time he or she engages the bot.

Conversational AI remembers past interactions with each individual customer, whether they occurred online, over the phone or via SMS. It can also pull from the customer’s personal information, products owned, order history, and other data to create personalized conversations. (“I see last time you ordered a side salad. Would you like to include that in this order, too?”)

Multi-intent understanding

Conversational AI: YES      Dumb Bot: NO

Let’s take a sample conversation with an IVR:

IVR: “How can I help you?”
Customer: “I need to update my credit card, but I’m locked out of my account.”

A common chatbot would likely respond to this two-step request by picking up on the first part (“You want to update your credit card information. Is that right?”) and ignoring the second. It’s up to the customer to repeat their lockout issue once the bot asks if it can help with anything else.

Conversational AI picks up on both requests, circling back to address one after it has resolved the other. Because the AI is capable of topic switching, the customer can deviate into multiple questions or issues throughout in the interaction, and the AI can eventually bring it back on track to the primary intent. This eliminates the need for customers to repeat themselves and reduces the chances of calling back to fix leftover issues.

Integration, scalability and consistency

Conversational AI: YES       Dumb Bot: NO

Businesses spent $190.8 million on chatbots in 2016 alone. Over the years, they’ve installed standalone bots—adding one platform here, a different one there—scattering disconnected mouthpieces across their enterprise. It’s awkward for a company to scale up disparate conversational tools, and it’s costly to rip and replace the bots they bought with a whole new system.

With AI, chat interfaces and virtual assistants throughout the enterprise can draw from the same data sources and speak the same words. Customer interactions with automated platforms will have consistent quality and cadence across the brand, whether customers are calling a sales line to order a product or texting tech support to troubleshoot an issue.

Now let’s see how the two technologies stack up:

These capabilities only scratch the surface of what conversational AI can do in an intelligent CX system. An AI platform can generate millions in ROI for a business while improving CX (check out our conversational AI case study).

So what is a chatbot? Going forward, the only right answer to that question is “a glorified FAQ.” Looking for the right answer for your business? Try CSG Conversational AI.

Amy Allen

Amy Allen

Digital Transformation | Conversational AI — Product Management

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Link: Conversational AI vs. Chatbots—What’s the Difference?