There are three main types of chatbots:
This is the simplest type of chatbot. Users interact with such bots by clicking on buttons and selecting predefined options. To give relevant answers to the query, these chatbots require users to make a few selections. These bots have a longer user journey, and they are the slowest option to guide the customer to their satisfaction.
These bots work great when it comes to qualifying your leads. The chatbot asks questions for users to answer, before analyzing the collected data to give a reply. However, for more advanced queries with several conditions or factors, these chatbots aren’t always the best solution.
Intellectually Independent Chatbots
These chatbots use Machine Learning (ML) which helps the chatbot learn from the user’s inputs.
ML is the ability of the computer to analyze the data, learn from it, recognize patterns, and make a decision with minimal human interference.
Intellectually independent chatbots are programmed to understand specific phrases and keywords that trigger the bot’s reply. Over time, they train themselves to understand more and more questions.
For instance, you ask a chatbot: “I am having a problem with signing in to my account”. The bot would understand the words “problem” “signing” “account” and provide a predefined answer based on these.
AI-powered chatbots are the combination of the best features from Rule-based and Intellectually Independent chatbots.
Artificial Intelligence (AI) is a simulation of human intelligence. AI is the area of computer science that focuses on creating intelligent machines that work and “think” like people.
AI-powered chatbots can interpret free language, coupled with a predefined flow to make sure they solve the user’s problem. They can remember the user’s preferences and the context of the conversation. These chatbots can shuffle through one point of conversation scenario to another when needed and address random user requests at any moment.
These chatbots use Machine Learning, AI, and Natural Language Processing (NLP) to understand users.
NLP is the ability of the computer to understand and analyze human speech, find the right response, and reply in an understandable human language.
The goal of NLP is to make the human-to-machine interaction as realistic as possible. With the help of NLP, people can freely interact with chatbots regarding their queries.
NLP involves 2 further processes:
Natural Language Understanding (NLU): The ability of the chatbot to understand a human input (text/speech) and the process of converting that input into structured data for a machine to understand.
Natural Language Generation (NLG): NLG transforms structured data into text.
For example, a user writes to a chatbot “What is the weather in Barcelona today?”. In order to give a reply, the chatbot breaks down the sentence into Intents and Entities.
Intent: an action or a request the user wants to perform or information he/she wants.
Entity: a detail that compliments the Intent. It can be a date, location, color, size, flavor, etc.
So, using the same example the Intent would be “weather”, and the entities would be “Barcelona” and “today”.