How To Make A Chatbot Using Natural Language Processing?
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How To Make A Chatbot Using Natural Language Processing?

In the early days, chatbots were just new digital devices in the market with no practical utility and used to experiment with the market. But with time they were also evolved and thus became a vital tool in the corporate world.

The development and maintenance of a chatbot is an effort-intensive, time-consuming, and costly task. Still, many startups and established organizations are trying to experiment with this incredibly humanitarian and innovative technology.

The integration of interactive chatbots into corporate platforms or websites is very popular and used by almost every organization. These chatbots are capable of answering different and out-of-the-box questions. This device ensures that customers get all the necessary and required information anytime and anywhere.

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The integration of these trendy chatbots in business websites or other platforms is inevitable. Nowadays several companies are using this system because they want their customers to have access to the right information anytime and anywhere.

Chatbots respond back to queries quickly with relevant information and thus speed up the response time. This helps companies can save a lot of money that they usually spend on customer service. It also enables agents and employees to concentrate on other challenging tasks.

Many well-known brands like MasterCard have also launched their own chatbots. From American Express’s customer service to Google Pixel’s call screening software, chatbots are transforming the corporate world in surprising and fascinating ways. This way they ensure that 24/7 availability is provided to all customers.

Well, before understanding how you can take benefit from a chatbot made using NLP in python, it is important to understand a deep learning chatbot.

What Is Meant By Deep Learning Chatbot?

A deep learning chatbot uses natural language processing to map the user input to the intent in its database to categorize the message to make a predetermined response. The primary goal behind all this is to make the chatbot intelligent and behave as human as much as possible.

A chatbot is an intelligent device that enables machines to analyze, grasp, and answer through Natural Language Understanding. It is based on refined deep learning and natural language understanding (NLU).

Modern chatbots made in python using natural language processing (NLP) behave almost the same as humans and one cannot distinguish them at the front end. Our daily lives and companies can be significantly facilitated or made easier because of the use of NLP in chatbots. As chatbots can now identify the exact intent of users, just as people can comprehend each other’s language.

Read more: Business Analytics, Data Science, Machine Learning and AI- How have they raised up the technological world?

What Are The Different Types Of Chatbots?

Based on different programs and tools, chatbots made using natural language processing are of two types:

Scripted chatbots:

These chatbots work on a set of pre-written rules in a conversational flow. When a user clicks one of the mentioned questions, it responds to it with the scripted answer stored in its database. If a user writes a query out of the box, this type of chatbot may not be able to answer it. 

Artificially intelligent chatbots:

These chatbots are based on natural language processing and they are made very human-like. These AI chatbots learn and expand their knowledge base with every new interaction. And this is why they are able to respond to the exact meaning of the query.

Its characteristics include communicating with humans via text messages or sound methods. And this becomes possible due to the computer program or artificial intelligence used in it. These NLP-based chatbots are usually designed to support customers on websites through the phone.

Such chatbots are used in messaging or eCommerce apps to order food/products, buy tickets, message automatically, or show weather stats. Some famous examples of apps that use AI chatbots include Slack, Telegram, eBay, Lyft, etc.

Challenges Faced By NLP-based Chatbots

Earlier computers were used for complex calculations but now they have also evolved with time. With the invention of Natural language processing, computers nowadays are capable of understanding and reacting to human language. Well, the human language is chaotic which makes it difficult for chatbots to understand and respond.

Here are some of the elements mentioned below which make the understanding of a natural language processing chatbot challenging. 

  • Abbreviations
  • Omitting punctuation rules
  • Synonyms, slang, homonyms
  • Different accents
  • Misspellings

We, humans, can understand the meaning behind body language, intonation, content, and expressions. We can have an understanding of the working of a machine using NLP till it does not have such linguistic characteristics. NLP suggests teaching the machines to understand the speech irrespective of distractors.

Read more: 5 Kinds Of Artificial Intelligence

Ways To Create NLP Chatbots: Custom Development vs Ready-Made Solutions

There are different methods available to develop a chatbot. Entrepreneurs can connect with top app development companies in India and other corners of the world to know which method is best for their business. Let’s talk about each solution one by one and discuss its advantages and disadvantages.

1. Ready-made solutions:

Many chatbot platforms allow you to customize and build chatbots for yourself or your business. It is a quite common and useful solution for business owners who do not need complex and technical chatbots. It is ideal for those who possess fewer coding skills and want to maintain them by themselves.

Pros of ready-made chatbot solutions:

  • Simple and quick: When you need to construct an NLP chatbot but don’t have the time or resources to write code, ready-made tools are ideal.
  • Integrations: The majority of ready-made systems provide built-in interfaces with messaging platforms like Messenger, Telegram, and Skype, as well as third-party services like payment gateways.
  • Budget-friendly rates. It is feasible to locate chatbot-building platforms that are inexpensive or even free to use.
  • Cons of ready-made chatbot solutions
  • Poor functionality: These chatbots only have a few basic features and are made with simple logic.
  • Difficult to customize: Extending functionality or adding new features are not available in these chatbots.

Custom-Made Chatbots:

If your business needs an advanced chatbot that is capable of personalized API integrations, you should go for custom-made chatbots. These are created with a set of features and custom logic to meet your business requirements.

Pros of custom-developed chatbots:

  • Customization. You may make your NLP-powered chatbot complicated and distinctive with custom programming. There are no limitations: simply undertake a discovery phase to learn more about your target audience and select the most appropriate features for your own chatbot.
  • Expertise. You can select a team with experience in specific technologies. You may, for example, go with a company that specializes in Python or chatbot development. The chatbot professionals will be able to customize your chatbot software to meet your specific requirements.
  • Testing and maintenance. When you pick custom development for your chatbot, you can rest assured that your chatbot will not only be developed but also tested and maintained in the future.

Cons of custom-developed chatbots

  • Time for development: The time taken to develop a customized chatbot can range from a few hours to several weeks. This also depends on the characteristics you want to add to your chatbot.
  • Cost of development: For ready-made solutions, you only have to pay the monthly or annual charges. But NLP-based customized chatbots will charge you for each NLP feature.
  • Development of a custom chatbot: It will be difficult if you are not an expert or don’t have anyone in your in-house team with professional development skills. In that case, you should hire an offshore chatbot development company.

How To Build A Chatbot Using NLP (Natural Language Processing)?

In order to make your NLP chatbot read, understand, interpret, generate, and send a response to the query of human beings, five stages should be present in it. These stages are tokenizing, identifying entities, normalizing, dependency parsing, and creation. Let’s see how chatbots are built.

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Analysis of Business Logic

This phase is crucial so as to collect and understand clients’ needs and in this step, the client interacts with the development team. There are various processes that take place in order to understand the business logic. The team will conduct an analysis phase to study the competitive industry and decide the required functionalities for your chatbot to stand ahead of the competition. After all this, they build the business logic of the product.

Channel & Technology Stack

You can use various platforms as a base to create a chatbot such as Twilio, Viber, Telegram, Google Chat, etc. Various popular technologies used to develop chatbots with NLP tools are as below:

  • Python – It is an object-oriented programming language used to create the architecture of the chatbot.
  • Twilio – This platform allows developers to use its API to write code to send and receive messages, make and attend phone calls, and other communication functions.
  • Pandas – It is a software library with functions for data analysis and manipulation used by the Python language
  • SpaCy – It is a software library with complex functions for advanced natural language processions
  • TensorFlow – This again is a library having functions used for neural network and machine learning tsks
  • Viber, Telegram, Or Google Chat APIs – These are APIs that are used to connect the front-end of chatbot to the websites or messengers.

Development & NLP Integration

Creating a fully-functional chatbot involves two basic steps i.e. development of a front-end chatbot and integrating it with the service providers’ API. After the development of a chatbot, NLP can be added by integrating AI.


This step is highly important to avoid future problems. Manual testing is done to check if AI and NLP-based chatbot is working properly. Before manual checking, you should test the code, debug and fix any errors found.

Final Thoughts:

Chatbots based on Natural Language Processing and Artificial Intelligence attract more users, improve your brands’ reputation, save time and money. The more users visit your website, the more profit you’ll earn. There are several app development companies in India and all over the world that can help you get a customized chatbot.

It’s high time to move forward and work latest and highly useful technologies to keep yourself updated and meet customers’ requirements. NLP-based chatbots are one of the profitable trends that you should also incorporate into your business.

Author Bio:

Ranjit Singh is the founder & Director of RV Technologies and has been an avid technical blog writer too. His passion for business and writing informative articles on mobile app development is commendable. With years of experience in the IT industry, he has been able to bring up the best marketing solutions through app development that guides you at each and every step. 

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