When it comes to technology, each advance is dependent on some other technological advance. For example, Conversational Artificial Intelligence (AI) automates two-way, human-like conversations at scale. But that capability requires a concert of technologies to enable it including artificial intelligence, machine learning, and robot process automation. But there’s something else at play too—Natural Language Processing (NLP).
Let’s take a closer look at NLP, what role it plays in Conversational AI, and how these technologies drive better business outcomes for revenue-generating teams.
What Is NLP in AI?
In a way, Natural Language Processing is exactly what it sounds like—the ability for a technology to process everyday language. This can be written text (as in an email, text message, or website chat window) or speech (like a phone call or voice-activated assistant).
But NLP is further made up by Natural Language Understanding (NLU) and Natural Language Generation (NLG). The former is the ability to perceive and understand communications coming from a contact. This can be as simple as taking orders. The latter is the ability to generate text or speech. It’s only once NLU and NLG come together that you can engage contacts into two-way conversations; understanding language coming in and generating language going out.
That’s just the function, of course. What you do with that function is what businesses are interested in.
How Businesses Use NLP and Conversational AI
Now that we’ve covered the topic generally, let’s drill down into what this means for business users. By automating the ability to perceive, understand, and respond to conversations with leads and customers, organizations offload routine conversations onto an AI.
It takes time to craft a personalized email to a prospect or customer. Usually, this only takes a few minutes for each interaction. However, this becomes a problem of scalability when you have hundreds or even thousands of contacts to interact with. By automating these interactions, employees can spend less time focusing on crafting redundant messages and more time focused on high-value tasks.
Then again, Natural Language Processing in AI isn’t just about improving efficiency. Conversational AI is ultimately about driving revenue opportunities. These technologies work together to automate interactions and engage contacts in natural back-and-forth dialogues pushing towards the next best action.
For instance, delivering a personalized first-touch to hundreds of webinar attendees is difficult for even the most dedicated Marketing and Sales teams. But Conversational AI makes it scalable to ask leads if they have questions and are interested in meeting with a Salesperson to get those answered. A powerful AI solution engages attendees to determine which are ready to take action and which need more time or attention.
Natural Language Processing is an integral part of Conversation AI’s ability to engage contacts, drive revenue opportunities, and augment revenue-generating teams of business professionals.
Interested in understanding what Conversational AI can do for your revenue-generating teams? Check out our webinar: The AI Revolution Is Coming to Every Stage of Your Buyer’s Journey.