How NLP helps creating chatbots

NLP helps creating chatbots

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Do you want to create a chatbot, but you don’t have lots of ideas on how to start? It is not the simplest thing. However, you may begin by considering the creation of an AI and NLU-based chatbot. We will explain why NLP and chatbots are a great match and give you some hints that you can use for your strategies.

Are you ready? Let’s start!

What chatbots and NLP are 

To better understand the power and the capabilities of chatbots and NLP, it’s better to introduce both terms and their relationship.

Chatbots, according to Investopedia:

“A chatbot is a computer program that simulates human conversation through voice commands, text chats, or both. Chatbot, short for chatterbot, is an artificial intelligence (AI) feature that can be embedded and used through any major messaging application. There are several synonyms for chatbot, including “talkbot,” “bot,” “IM bot,” “interactive agent”, or “artificial conversation entity.”

Nowadays, they are a colossal help for brands and marketing strategies in customer care because, thanks to automation, they can easily interact with clients. If trained properly, they can also sound and look like human beings. Here is where natural language processing and natural language understanding, NLU for short, as we will see in a minute. Chatbots come in different forms – however, don’t mistake them for virtual assistants: they are two different things!

On the other hand, NLP is, as we were saying in our last article, “the ability of a computer program to understand spoken and written human language”.

It is a subfield of artificial intelligence that helps machines and algorithms to understand better human language and, in this way, to communicate with us more efficiently.

Of course, it is one of the essential elements in creating chatbots! We can find another couple of fields inside NLP: NLG – Natural language generation – and NLU – Natural language understanding. Both are essential to building an artificial intelligence-based chatbot as realistic as possible.

NLP and chatbots: why do they need each other?

There are two main kinds of chatbots:

  • Rule-based Chatbot. In this kind of chatbot, its conversations and capacities are limited because it only responds to a set number of requests. Its intelligence ends where the data set ends, and it reacts to specific requests and only to particular answers.
  • AI Chatbot. That is an AI-enabled type of chatbot. It learns from conversations, understands the question, and can answer with the information it has. They are usually also known as Virtual Agents, Virtual Assistants, or Conversational Agents.

AI chatbots are preferable because they mimic how human beings act and respond. Most importantly, if they can handle a conversation with a high understanding of human language and its nuances, it’s all thanks to NLP.

That is why chatbots need NLP: not only because it is an essential component of their functioning but also because it is the primary way developers can make them realistic, efficient, and responsive to the human language. NLP is the only way in which we can build a chatbot that feels like a human being, and all of this happens thanks to language understanding.

Three ways in which an NLP and AI-based chatbot helps brands

The theory is interesting, but how can we use NLP and chatbots for marketing strategies? There are several ways to do it, but we will see three of the most important and common ones.

Smoother conversation for higher satisfaction

When a chatbot can communicate with smooth, plain language, it makes it easier for customers to interact with it, be more patient, and generally feel the brand’s right mood. 

Moreover, a conversation that goes as well as possible is also positive reinforcement for customers to come back, which helps increase the brand’s loyalty, popularity and commitment.

Lower costs

It may look less fancy than other reasons, but using NLP and AI-based chatbots for brands, especially for customer care, means an essential reduction in costs.

Not only in terms of the workforce but also in terms of time: employers can focus on different tasks, only to intervene when it’s needed.

More data to work with

If you have ever collected data, you know how unstructured and sparse they might be. It is an issue, especially when you need to have a clear vision of your market and business results. In this case, NLP helps because it can assist you in analyzing all the precious bits of information you collected from the interaction between the chatbot and customers.

Conclusions

Is NLP a helpful tool to build chatbots? Better to say, it is the only and truly efficient way to do it. Artificial intelligence and machine learning contribute to making more complex and responsive versions of chatbots that will guarantee a more human-like feeling. That is a massive help for customer service: have you ever tried it? If not, check our website!

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