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What Conversational Intelligence Means for Customers and Businesses


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Conversation Automation
Published 09/29/21
4 minutes read

There are many different types of artificial intelligence (AI). People are familiar with common examples such as chatbots, voice-activated assistants, and marketing automation tools. But there are other innovations in AI helping businesses better connect with customers and drive revenue opportunities.

Conversational Intelligence, for example, has been around for a while but was only recently acknowledged as its own category. This is fantastic news because Conversational Intelligence isn’t quite like other types of traditional AI. Conversational Intelligence delivers personalized human-like conversations at scale. This differs from other technologies which require a range of pre-determined conversation flows.

Also known as Conversational AI, this technology provides more personal interactions between potential customers, accounts, and contacts without having to engage an actual member of your company’s teams. This is extremely helpful for revenue-generating teams who simply do not have the capacity to deliver the necessary personalized attention to engage every lead or customer. Rather than letting opportunities go unnoticed, Conversational AI provides a way to drive conversations from the growing number of high-impact customer conversations, which is essential as more interactions occur at volumes that Marketing, Sales, and Customer Success teams simply can’t manage on their own.

Let’s look at a few types of Conversational Intelligence technologies, what benefits Conversational AI offers, and some important statistics driving the popularity of this innovative approach to AI.

Types of Conversational AI

There are several primary types of Conversational AI on the market. All of these components continue to change and evolve, and new types will likely emerge over time. It’s also important to understand that there are some overlaps in these technologies:

  • Automated speech recognition (ASR) takes spoken content and converts it to text, so the input can be verified.
  • A dialog manager is typically the most complex as it interprets the input to make a decision about what should be done, then executes that decision to answer a query. This is replacing the more traditional types of chatbots with predetermined answers.
  • Natural Language Processingis AI’s ability to understand what a person is saying to pull out the pertinent information.
  • Text-to-speechturns typed text into a spoken automated voice.
  • Intelligent Virtual Assistants,also known as AI Assistants, act as virtual team members helping to engage customers at scale, in hopes of elevating revenue opportunities.

Customers are less interested in dealing with traditional AI that offers only a rudimentary, predetermined answer that doesn’t address their concerns or needs. And it’s up to businesses to meet customer expectations. This is fueling the popularity of more sophisticated AI Assistants that use Conversational AI to engage contacts, answer questions, determine intent, and accelerate opportunities. This is a boon for customers, who expect a certain level of attention when they need it—as well as businesses, who want to connect with customers at the right time.

The Benefits of Conversational Intelligence

Conversational AI uses Machine Learning and Natural Language Processing (NLP) to create something that can interact with people on a more in-depth level. While chatbots provide pre-programmed exchanges, Conversational AI engages contacts in authentic two-way conversations without the need for business professionals to program anything. This means Conversational AI can handle complicated questions, provide detailed answers, and deliver personalized experiences at scale.

Conversational AI acts like a real person and responds with more intuitive answers, determines intent, and tailors responses based on a wealth of data built into the solution. This provides deeper insights that are absent from the simpler forms of AI.

Better still, Conversational AI can determine intent and match it with the next best action. Have a lead interested in learning more about your offerings? The AI can pass the hot lead over to Sales at the moment they express interest. Have a customer lagging behind in product usage? The AI can persistently reach out to see if the customer has questions, needs help, or requires additional services to accomplish their objectives.

So, not only does Conversational Intelligence offer better customer experiences on a larger scale, but it also autonomously identifies and boosts revenue opportunities.

Conversational AI in Stats

It’s always wise to keep an eye on technological innovations to see what’s working and what needs time to mature. Fortunately, Conversational AI is battle-tested via real-world interactions with leads and customers. This means that businesses see a quick time-to-value. This is particularly true in today’s changing online environment in which self-service and digital-first interactions are the norm.

Digital-first interactions are now the dominant way customers learn about your brand and its offerings. This shift puts the customer in the driver’s seat, which has its benefits. But it also has its drawbacks in that the customer’s experience is largely impersonal. In fact, 70 percent of companies do not have a personalized approach at scale. Conversational AI bridges the gap between different phases of the customer lifecycle to meet customer expectations and discover more revenue opportunities at scale.

Interested in exploring the difference Conversational AI can make for your business? Check out our webinar with Forrester Research, Tech Talk: Leveraging Virtual Assistants and Conversational AI to Enable Buyers and Sellers.

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