The Complete Chatbot Glossary for Beginners
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The JetSpring Chatbot Glossary: Chatbots have been around for decades now, but most people aren’t familiar with the terminology relating to them. 

If you’ve ever interacted with an online customer support bot or if you’re a business owner yourself, you probably know how to use chatbots. But do you know the difference between an attribute and an entity? Here’s a beginner’s guide with everything you need to know about chatbots.

If you’re thinking of implementing a chatbot for your business, or if you just want to get more insight into the world of AI, this glossary is a great place to start.


An attribute is a piece of information, such as the user’s name, that the chatbot can refer to later in a conversation.

Artificial Intelligence (AI)

Artificial intelligence (AI) is the ability of a computer to emulate actions associated with humans. The primary goals of implementing AI are to enhance learning, reasoning, and perception. AI has applications in a wide variety of industries and situations一from self-driving cars to epidemiology.


Autoresponders are the instantaneous messages businesses can implement in their chatbots. Customers expect immediate replies, so pre-programming them as autoresponders can improve customer experience.


A chatbot is a software tool that is used to conduct online conversations between a human and a computer, often used for customer support or sales purposes. Chatbots can be added to websites or integrated with other messaging apps, such as Facebook Messenger.

Chat Log

Chat logs, or chat transcripts, are the text of a full chatbot conversation. It’s important to track these to note frequently asked questions and common concerns that customers have.

Chat Widget

A chat widget is a little button that often appears in the bottom right corner of a website and leads to the conversation. It’s best practice to customize the widget to match your branding.

Screenshot of JetSpring website highlight the chat widget in the bottom right

Chat Window

A chat window shows the chat conversation. The user is able to scroll through previous messages and send new ones. In some chatbots, the window will display how long the conversation has been going on or include a button to connect the user with a live person.

Screenshot of JetSpring website showing the chat window

Compulsory Input

Compulsory inputs are required pieces of information users must provide before using a chatbot. These are customizable on the backend, so companies can choose what information they want to gather, whether they just want a name to make the conversation more personable, or if they want contact information to follow up later.

Conversational User Interface (UI)

Conversational UI includes the visual appearance and design of the chatbot. From the colors and logo to the buttons and widget, make sure your chatbot’s conversational UI is a cohesive extension of your website.

Conversational User Experience (UX)

Conversational UX includes the intangible factors that affect the user’s experience of interacting with the chatbot. For example, this could include the chatbot’s personality, the speed between messages, and the diction used.


Entities are pieces of information that the chatbot needs to recognize in order to provide an answer to the user. Entities function similarly to FAQs: 

User: What color t-shirts do you have available?

Chatbot: We have red, green, and blue t-shirts available.

In this example, “color” and “t-shirts” are entities. The chatbot recognizes them and retrieves the relevant information.

Flow-based Chatbot

Flow-based chatbots are chatbots that function simply as a triaging flowchart or decision tree. There’s no AI involved, which limits the types of interactions users can have with them, but they’re a low-cost solution for identifying a customer’s issue and pointing them in the right direction.


Intent refers to what the user meant in their message to a chatbot. It gets at the root of what the person was asking and serves as the basis for the chatbot’s response.

Machine Learning (ML)

Machine learning is a subset of artificial intelligence that allows chatbots to learn from human interactions to become more efficient and effective over time. It includes the process of teaching a bot more information through inputting data or observing past mistakes.

Natural Language Processing (NLP)

Natural language processing is another subset of AI. It’s used in chatbots to recognize and respond to human speech and sentiment. 


Pop-ups are visual cues used on websites to let visitors know that there is a chatbot available. 

Screenshot of JetSpring website showing chat pop-up


Training a chatbot refers to the ongoing practice of feeding the chatbot new information, reviewing chat logs to find areas of improvement, and other updates. Training allows your chatbot to become an even better tool for your customers.


An utterance is anything that a person says in a conversation with a chatbot.

If you’ve read through this chatbot glossary and are still confused, try out ours! You can see the real-life applications of these terms, and we can answer any outstanding questions you have.


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