Chatbots Glossary 35 Terms You Need To Know

Chatbots Glossary – 35 Terms You Need To Know

Chatbots have gone so mainstream that most people know what they are and their various applications. However, not many people can talk fluidly about it without asking for explanations on certain concepts. Here are a few chatbot-related terminologies that can help change that. These terminologies will definitely help people to share chatbot-related ideas and information more effectively. Let’s begin!

1. Artificial Intelligence (AI)

AI is a branch of computer science that enables systems to perform tasks that typically require human intelligence. In regards to chatbots, AI helps them conduct more meaningful and intelligent conversations. 

2.  Aggregator Bot

An aggregator bot is a centralized chatbot which unifies multiple individual chatbots together and prevents the challenges  that arise due to fragmentation of chatbots across functions.  

3. AI agnostic bots

AI agnostic bots don’t leverage AI to deliver responses. They interact with users based on a set of predefined rules.  They can’t answer any questions outside of these rules

4. Broadcast

Broadcast is a message that is sent to all the users interacting with any of the organization’s chatbots irrespective of the channels.

5. Channel

Channel is an authorized medium for the chatbot-user conversation. For e.g.: Skype, Facebook Messenger, SMS, web chat window, and email etc.

6. Chatbot building platforms

A chatbot builder platform is a toolset with which you can quickly and seamlessly build, deploy and manage custom AI chatbots for your enterprise. 

7. Chatbot Framework

A bot framework is a toolset which helps you develop chatbots with predefined functions and classes. Frameworks are usually used by developers as they involve some programming or coding.

Learn More: Comparing The Top Bot Development Frameworks 

8. Chat Log

Chat Log is the history of the entire recorded human-to-chatbot interaction.

9. Compulsory Input

Compulsory Input is a piece of information that the user has to provide before they can move on to the next stage of the conversation. They usually are Order Tracking Number, Employee ID, or Date of birth etc.

10. Context

Context is the chatbot’s understanding of the scenario provided by the user.

11. Conversational User Experience (CUX)

CUX is the quality of the interaction between humans and computers, which can be in the form of chat, voice, or any other media. An excellent conversational UX helps users reach their goal in the shortest time with maximum end-user experience. 

Read More: A Quick Guide To Creating An Conversational User Experience  

12. Conversational User Interface (CUI)

CUI enables the user to interact with a computer in a more social manner via messages, and conversations. It is a major change from traditional interfaces which involve syntax-based commands or clicking elements.

13. Corpus

Corpus refers to all the stored information about a particular Intent.

14. Decision Tree

With Decision Trees, chatbots help users find what they’re looking for.  Using a step-by-step process, they help identify the right answer to the user’s question in a conversational way. The initial question in the question acts as the “root” of the tree. 

15. Deployment

Deployment is the process of putting a chatbot in a communication channel where it can start interacting with the user.

16. Entity

Entity is the data that can be extracted from the Utterance. Common entities include names, organizations, places, and quantities.

17. Fallback

Fallback is the case in which the chatbot doesn’t understand the user’s context. It can be handled with a default answer that admits failure, specifying that the chatbot is still learning.

18. Human Handoff

Handoff refers to the scenario in which the conversation is transferred from the chatbot to a human agent. This usually happens when the chatbot is unable to handle the complexity of the conversation, or due to the preference of the user.

Read More: Human Handoff In Service Desk Bots 

19. Intent

Intent refers to the goal the user has in mind when asking a question or sending a comment. Identifying user intent is critical to a chatbot’s success.

20. Knowledge Base

Knowledge base is essentially the brains behind the chatbot. It equips a chatbot with the information it needs to deliver the right responses

21. Live-Ops

Live-ops refers to the live chat by a customer service agent. Chatbots can be configured to transfer the conversation to a live agent if the bot is unable to deliver a satisfactory response.  

22. Machine Learning

Machine learning enables chatbots to learn from the past user conversations and deliver personalized and better responses in the future.

23. Maintenance

Maintenance means analyzing the new learnings and actions of the chatbot.

24. Multi-factor Authorization (MFA)

MFA refers to the use of more than one method to authenticate a user’s identity.

25. Multilingual Chatbot 

A Multilingual Chatbot allows enterprises to converse with users speaking various languages. They are capable of conversing in multiple languages – not just translation.

Learn More: Multilingal Chatbots: Benefits And Key Implementations 

26. Natural Language Processing (NLP)

NLP is a technological process that allows chatbots to derive meaning from user input, either text or voice-based, and then act on it.

27. One-time Authorization

One-time Authorization is the process of validating the user’s identity for only one session.

28. Optional Input

Optional Input is a piece of information the user gives to the chatbot, that is not crucial to the conversation.

29. Quick Replies

Quick Replies are the suggestions that appear after a chatbot’s response, which prompts the users to continue the conversation as per the predesigned pathway. They can be questions, answers, or assertions, depending on the conversation flow and voice tone.

30. RPA Bots

RPA bots refer to the integration of front office chatbots with back office RPA software. This enables end-to-end automation and chatbot integration with legacy systems.

Learn More: RPA Bots: Understanding The Chatbot And RPA Integration 

31. Sentiment Analysis

Sentiment analysis helps a chatbot to understand the emotions and state of mind of the users by analyzing their input text or voice.  

Learn More: Understanding The Role Of Sentiment Analysis In Chatbots 

32. Session

Session is the time period of the interaction between the user and the chatbot.

33. Training Phrases

Training Phrases are the simplified and annotated sentences used to train the Machine Learning algorithm of chatbots. They are associated with an Intent and mapped through Entities, helping the algorithm learn and improve.

34. Utterance

Utterance is the input provided by the user during a conversation with the chatbot. They are different from Training Phrases since they are spontaneous.

35. Voice Assistants 

Unlike chatbots which converse with users via text, voice assistants or voice bots interact with customers and employees via voice. Amazon Alexa, Microsot Cortana, Google Assistant are some examples of voice assistants. 

Learn More: How Voice Assistants Are Transforming The Enterprise Workplace? 

While these are some key chatbot terms you need to know, there are many others that are equally important.

If you’d like to learn more about this topic, please feel free to get in touch with one of our enterprise chatbot consultants for a personalized consultation.