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What Is Conversational AI? 3 Questions Answered


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Conversation Automation
Published 07/15/22
5 minutes read

Everybody’s talking about Conversational AI—especially as more businesses of all sizes and across industries adopt the technology to innovate customer communications.


But what is Conversational AI? And why is it important to customer-facing revenue teams?

Let’s answer three common questions about Conversational AI and the value it offers to businesses and their customers.

What Is an Example of Conversational AI?

Conversational AI is a type of artificial intelligence that automates two-way communications between AI and contacts.

Common examples of Conversational AI include:

  • AI chatbots: Rules-based website chat is mostly used for fielding frequently asked questions and helping out customer support teams. This technology is leveraged by a variety of industries but is especially useful to ecommerce websites.
  • Voice assistants: These voice assistants use microphones to recognize spoken commands such as conducting online searches or managing connected technologies like lights or thermostats. This technology is mostly used in consumer products such as Amazon Alexa or Siri from Apple.
  • Virtual call center agents: As you might be able to tell from the name, this technology is used by a handful of industries but is especially useful for call centers. By recognizing spoken words and phrases, these virtual agents help customers while cutting down the amount of time it takes for employees to interact with customers.
  • Intelligent Virtual Assistants: A more mature form of Conversational AI, Intelligent Virtual Assistants engage contacts in human-like, two-way conversations that drive towards a revenue-generating event. IVAs communicate across multiple channels including email, SMS, and website chat. This technology is used by a wide variety of industries including technology, telecommunications, business services, financial services, health and wellness, higher education, insurance, manufacturing, retail, and entertainment.

Undergirding many of these Conversational AI solutions are Natural-Language Processing and Machine Learning. NLP (which includes Natural-Language Generation and Natual-Language Understanding) enables Conversational AI solutions to understand everyday language and autonomously respond in a way that feels natural and normal. Machine learning, on the other hand, helps the solution to learn over time. With both of these technologies working in concert, Conversational AI gets better over time and with each interaction. This means that the best Conversational AI is battle-tested in real-world interactions, which makes it better at real-world interactions. Now that’s a positive feedback loop!

While each of these technologies has its place, the two most common forms of Conversational AI are rules-based chatbots and Intelligent Virtual Assistants (IVAs).

What Is the Difference Between Chatbots and Conversational AI?

Just because chatbots and Intelligent Virtual Assistants fall within the same category, doesn’t mean they are created equally. 451 Research, part of S&P Global Market Intelligence, defines the difference between these two technologies this way:

“Chatbots are a familiar piece of the customer experience landscape; they provide a basic solution for automating simple recurring requests. They can handle high-scale interactions in low-stress environments at a low cost. However, as customer interactions become more complex with multiple, nuanced intents and requests, businesses need to explore more advanced options that go beyond most chatbots’ ability and offer a more human-like, two-way interaction. These advanced systems – intelligent virtual assistants (IVAs) – enable a personalized experience that drives meaningful business outcomes across the entire customer lifecycle.”

In other words, chatbots are more suited for automating simple, repetitive tasks like answering FAQs or directing incoming customer requests. But Intelligent Virtual Assistants offer a very different experience: they actively engage contacts in deliberate conversations that drive towards a specific action, like turning a lead into a customer or retaining/growing a current customer. With IVAs, the conversations don’t need to follow a pre-defined path; the IVA adjusts to the contact’s responses.

Another important difference is that chatbots only operate on one channel: website chat. IVAs can communicate across several channels including email, SMS, and website chat. In time, it’s possible that Conversational AI could add communication via social media channels as that becomes a higher priority for customer-facing teams.

451 Research points out these technologies are still maturing and their use cases evolving. It’s possible that Conversational AI might reach a point where Intelligent Virtual Assistants act more like Intelligent Virtual Advisors. So rather than offload personalized interactions for customer-facing teams, these forthcoming Intelligent Virtual Advisors or Autonomous Assistants will be able to learn from customer inputs and historical exchanges to provide recommended actions for their human coworkers.

depth of intelligent virtual assistant iva experience


Why Is Conversational AI Important?

Conversational AI and Conversation Automation are incredibly valuable to consumers and businesses for the simple reason that these technologies automate business-critical communications. This can be as simple as automating answers to frequently asked questions or as sophisticated as motivating contacts through the customer journey. It all depends on your business needs.

Intelligent Virtual Assistants, one of the more mature forms of Conversational AI and Conversation Automation, proactively drive customer engagement in ways that generate revenue. Here are a few examples of how different customer-facing teams use Conversational AI:

  • Marketing and Sales: An IVA built for Marketing and Sales teams can promptly and persistently pursue leads and share relevant resources until they self-identify intent or ask to speak with a Salesperson. This means sales-ready leads are accelerated through the funnel even if they haven’t MQLed.
  • Customer Success: An IVA designed for Customer Success teams is best suited for autonomously driving product adoption, renewing current customers, or even expanding the footprint of existing customers.
  • Payments: IVAs are also growing in popularity for politely and persistently urging customers to complete overdue payments.

As you can see, there are a lot of benefits of passing two-way, personalized conversations over to a Conversational AI solution. Some of these benefits include:

  • Personalized conversations at scale: People-power is great for building relationships, problem-solving, and closing deals. But repetitive personalized outreach is best handed over to an innovative tech solution—especially when you have hundreds, thousands, or even tens of thousands of contacts to touch.
  • Best practices, baked in: When Conversational AI is built on machine learning and artificial intelligence, it actually does a better job of nailing repeatable tasks than people do.
  • Revenue acceleration: This is the ultimate benefit of mature Conversational AI solutions. By driving top-line growth, accelerating handraisers, and making the most of every opportunity, businesses grow their wallets. And who doesn’t want that?

With a better understanding of what Conversational AI solutions offer, businesses are better equipped to make decisions based on their needs.

Want to explore what Conversica AI Assistants can do for your Marketing, Sales, or Customer Success teams? Watch our on-demand webinar, Prioritizing Experience to Accelerate Opportunities in the Customer Journey.

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