7 min read

NLP: The chatbot technology that'll be a gamechanger for your business (even more than GPT!)

Customer Service Chatbots
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NLP, chatbots, AI... you've probably heard all these words before, and then immediately discarded them. Too high-tech. Too complicated. Not relevant for your business. However, behind the technical terms, there are some very real advantages. These technologies can help you boost sales by 67 percent, reduce costs by 30 percent, and increase customer satisfaction. Sounds good? We explain how that works!

If somebody asked you: "Could you use an NLP chatbot for your business?", you would maybe hesitate, and think, "That’s waaaaay too fancy for my company." However, if somebody asked you: "Could you use a technology that could cut your customer service costs by 30 percent, increase sales by 67 percent, and reach a customer satisfaction score of 91 percent?", you would most likely say: "Where can I get it?"

NLP chatbots might sound aloof but bring very real advantages to your business. And they're 100% safe to use! In the following, you'll learn how the technology works, how businesses are using it, and we'll show you the NLP chatbot that outperforms IBM and Microsoft. 

What is NLP?

NLP stands for "natural language processing" and is a subfield of artificial intelligence (AI) of computer science. Simply put, NLP enables a computer to understand human speech and text, and reply to them like another human would.  

Why is that necessary? Well, because humans speak a natural language, like English or French. Computers, on the other hand, "speak" a programming language, like Java or Python. Unless your clients are proficient at coding, human language has to be translated for computers to understand it, and vice versa. That's what NLP does.  

If you have ever talked to a customer service chatbot, or given commands to your GPS system in your car, you have probably already communicated with an NLP chatbot.  

How does an NLP chatbot work?

For chatbots to be able to communicate with humans naturally, they must be trained.  

When a customer calls a restaurant to order a pizza, for instance, the service agent goes into the call with a lot of background knowledge. The agent knows what types of pizzas there are on the menu, what ingredients can be exchanged, and the agent also knows what questions customers typically ask, from delivery time to forms of payment. For humans, that comes naturally because it’s the way we communicate.  

However, a chatbot has to be taught to interact in the same way. This usually happens in three steps.  

  1. Intent classification (understanding the customer) 
  2. Entity recognition (extracting specific information) 
  3. Dialog manager (giving correct replies / taking right actions) 

Intent classification

Intent classification means that a chatbot is able to understand what humans want. A restaurant customer service bot, for example, not only needs to be able to recognize if a customer wants to order a pizza or ask about the status of their delivery, but also what type of pizza they want.  

Of course, people have many ways of ordering a pizza. A person could say anything from: "I want to order a pie" to "What’s your best slice?" to mean the same thing ("I want a pizza!"). So, NLP chatbots have to be taught to understand different expressions and match them with the correct intent.