What is a chatbot
chatbot is software that simulates human-like conversations with users via text messages on chat. Its key task is to help users by providing answers to their questions. Chatbots can chat with multiple users at the same time and provide information within seconds. Because of that, they are now used on a wide scale to help both businesses and consumers communicate with each other on websites and mobile messaging apps.
How do chatbots work?
Chatbots are powered by pre-programmed responses, artificial intelligence, or both. Based on the applied mechanism, a chatbot processes a user’s question to deliver a matching answer. There are two main types of chatbots, and those types also tell us how they communicate. They are rule-based chatbots and AI chatbots.
Rule-based (also command-based, keyword, or transactional) chatbots communicate using predefined answers.They can be playfully compared to movie actors because, just like them, they always stick to the script. Rule-based chatbots provide answers based on a set of if/then rules that can vary in complexity. These rules are defined and implemented by a chatbot designer. At this point, it’s worth adding that rule-based chatbots don’t understand the context of the conversation. They provide matching answers only when a user uses a keyword or a command they were programmed to answer.
When a rule-based chatbot is asked a question like, “How can I reset my password?”, it first looks for familiar keywords in the sentence. In this example, ‘reset’ and ‘password’ are the keywords. Then, it matches these keywords with responses available in its database to provide the answer. However, if anything that is out the chatbot scope is presented, like a different spelling or dialect, the chatbot might fail to match that question with an answer. Because of this, rule-based chatbots very often ask a user to rephrase their question. Some chatbots can also transfer a person to a human agent when needed.
It’s worth underlining that rule-based chatbots can't learn from past experiences. They respond based on what they know at that moment. The only way to make a rule-based chatbot better is to equip it with more predefined answers and improve its rule-based mechanisms.
On the other hand, the limitations of rule-based chatbots make them a very useful tool for businesses. Rule-based chatbots are the cheapest to build and easiest to train. Companies introduce them into their business strategies because they help to automate customer communication. The behavior of rule-based chatbots can be also designed from A to Z. This allows companies to deliver a predictable brand experience.
An AI chatbot is a piece of software that can freely communicate with users. AI chatbots are much better conversationalists than their rule-based counterparts because they leverage machine learning, natural language processing (NLP), and sentiment analysis.
allows chatbots to identify patterns in user input, make decisions, and learn from past conversations.
Natural language processing
helps chatbots understand how humans communicate and enable them to replicate that behavior. It’s NLP that lets chatbots understand the context of the conversation even if a person makes a spelling mistake or uses jargon.
The sentiment analysis
helps a chatbot understand users' emotions.