Understanding the Potential of Different Chatbot Types

Chatbots are the future of customer service, and they’re already here. Chatbots have been around for almost 70 years. However, it was only recently that their popularity began to skyrocket due to advancements in technology and machine learning. Chatbots can help you automate your business processes by reducing costs and improving productivity–which is why many companies are starting to integrate them into their apps or websites.

Simple chatbots

The most basic of the chatbot types is the simple chatbot. These are the easiest types of chatbots to build, maintain, test, and deploy. They’re also easy to scale, making them a great starting point for beginners and veterans alike.

Simple chatbots are built with a limited set of features that respond with pre-programmed responses based on user input. This makes them incredibly easy to create: all you need is some basic programming knowledge and an understanding of how your app works at its core level.

Script-based chatbots

Script-based chatbots are programmed to respond to a set of specific questions or keywords. They can be built quickly and at a low cost, but they also have their limitations. For example, they’re limited in the number of responses they can give and are not recommended for complex use cases.

However, if you want to create a simple bot that offers basic functionality like answering basic questions and performing simple tasks like booking flights, then a script-based chatbot will work just fine.

Chat script

Chat script is a chatbot builder that allows you to create a bot in minutes. It is the perfect tool for creating simple bots, but also has advanced features such as:

Image recognition: Your customers can upload an image and the Chat script will extract text from it.

Natural language processing (NLP): Users can use natural language for conversations with their bots and get answers back in the same language.

Speech recognition: Users can talk to their bot via voice commands, even when they are not connected through Facebook Messenger, Slack, or Skype.

Natural language processing (NLP) based chatbots

Natural language processing chatbots are one of the most sophisticated chatbot types and they’re able to understand human language. They can recognize the meaning behind words, context and emotion. This allows them to carry on a detailed conversation with you without any technical knowledge required on your part.

NLP chatbots can understand the meaning behind words because they use machine learning algorithms that have been trained by data collected from previous interactions with humans. The more data that is processed through these algorithms, the more accurate they become at understanding what people mean when they say something specific or in certain situations.

They are also good at understanding context because there isn’t just one way to say something; instead, there are multiple ways that could mean the same thing at different levels of detail. NLP-based chatbots use this information when interacting with humans so as not to confuse them when asking questions or making statements that may seem unrelated but have some sort of connection between them when looked at closely enough.

Intelligent assistant chatbot

Intelligent assistant chatbots are the most advanced chatbot types. They can understand natural language and respond to user queries with a conversational tone. At this level, you can use the intelligent assistant for a wide range of purposes, including customer service, marketing, and sales.

For your intelligent assistant to be successful, it must be able to answer questions from users in a way that both makes sense and makes them want to continue using your bot again in the future.


You can see that chatbot types are not just limited to the ones discussed in this article. There are many other types of chatbots, including general intelligence and personal assistant bots. While there has been a lot of hype around these new technologies, businesses need to think carefully about how they can be used in real-life scenarios before making any rash decisions about whether or not they should invest in them.

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