• Artificial Intelligence (AI) :

This broad term refers to technology. It enables machines to mimic human cognitive functions. Some chatbots use simple rule-based systems. AI chatbots leverage machine learning to understand user intent & provide more natural conversations.

• Application Programming Interface (API) :

An API acts as a messenger between different software programs. Chatbots use APIs to connect with other applications and services. It can fetch data or complete tasks (e.g., booking an appointment).

• Attributes :

These are pieces of information associated with a user or conversation. In a customer service chatbot, attributes include a user’s name, purchase history, or current location.

• Chatbot :

It is a computer program that simulates conversation with humans. It can be through text or voice interfaces.

• Chatbot Builder : 

It is a software platform or a service that allows users to create and design chatbots. It can be without extensive coding knowledge.  These platforms often provide pre-built templates and drag-and-drop functionalities.

• Chatbot UX (User Experience) :

Just like any user interface, chatbot UX focuses on how users interact with the chatbot. This includes the conversation flow, design, ease of use, and overall user satisfaction.

• Chatbot Types :

There are different ways to categorize chatbots.  A common distinction is between rule-based chatbots (pre-programmed responses) and AI-powered chatbots (capable of learning and adapting).  Other categorizations might focus on functionality. For e.g., customer service, marketing) or platform (e.g., website chatbot, messaging app chatbot).

• Chat Widget :

This is the visual interface where users interact with the chatbot. It’s typically a chat window embedded on a website or messaging app.

• Cloning Tools :

These are functionalities within a chatbot development platform. It allows you to quickly create similar chatbots for different purposes. This can be useful if you need chatbots for various departments or languages with a similar core structure.

• Conversational Channel :

This refers to the platform where the chatbot interaction takes place.  Common conversational channels include websites, messaging apps. For e.g., Facebook Messenger, WhatsApp and even voice assistants (e.g., Alexa, Google Assistant).

• Conversational User Interface (CUI) :

This refers to the way users interact with a chatbot. It is like how a Graphical User Interface (GUI) works for traditional computer programs.  In chatbots, CUIs typically involve text chat or voice interactions.

• Decision Trees :

These are flowcharts used in some chatbots, particularly rule-based ones. The chatbot follows a series of predefined questions and branches. It is on the basis of the user’s answers to reach a specific response.

• Entities :

Within a user’s message, entities are specific pieces of information the chatbot can recognize.  For example, in the sentence “What are your business hours on Tuesdays?”, the entity might be “Tuesday” (referring to a day) or “business hours” (referring to a concept).

• Fallback :

This is a pre-programmed response used when the chatbot doesn’t understand a user’s query or can’t provide a relevant answer.  A good fallback response should acknowledge the confusion. It offers options, like directing the user to a human agent or suggesting rephrasing the question.

• Filters :

These are rules within a chatbot that determine which messages it should respond to.  Filters can be based on keywords, user attributes, or other criteria.  For instance, a chatbot might only respond to messages containing specific keywords or from authenticated users.

• Greeting :

This is the initial message a chatbot sends to welcome a user and introduce itself.  An effective greeting sets the tone for the interaction. It provides context about the chatbot’s purpose.

• Layered Communication :

This refers to a chatbot’s ability to handle complex conversations. It breaks them down into smaller, manageable steps.  The chatbot might ask clarifying questions or provide summaries of the conversation to ensure it understands the user’s intent.

• Machine Learning (ML) :

This is a type of AI that allows chatbots to learn and improve over time.  By analysing past conversations and user data, ML-powered chatbots can become better at understanding natural language. It also recognizes user intent & provides more relevant responses.

• Messenger Chatbots :

These chatbots interact with users on messaging platforms like Facebook Messenger, WhatsApp, or Telegram.  Messenger chatbots leverage the functionalities and features of these platforms to provide a seamless user experience.

• Natural Language Processing (NLP) :

This is a branch of AI that enables computers to understand and process human language.  NLP is crucial for chatbots to interpret user messages, extract meaning. It even generates natural-sounding responses.

• Natural Language Understanding (NLU) :

This is a subfield of NLP that focuses on a computer’s ability to understand the intent and meaning behind a user’s message.  It goes beyond recognizing keywords. It involves analyzing the context, sentiment & overall message to provide an appropriate response.

• Quick Reply :

These are pre-defined answer options offered by the chatbot within the chat window.  This can help users navigate the conversation easily & choose from common questions or requests.

• Sentiment Analysis :

This refers to the chatbot’s ability to detect the emotional tone of a user’s message.  By analyzing word choice and sentence structure, sentiment analysis can help the chatbot tailor its responses to be more empathetic or appropriate for the situation.

• Software Integration :

This allows the chatbot to connect with other software programs and services.  Through APIs, chatbots can exchange data, trigger actions, or leverage functionalities from other systems.  For instance, a customer service chatbot might integrate with a CRM system to access a user’s purchase history.

• Story :

In the context of chatbots, a story refers to a predefined conversation flow that the chatbot follows for a specific task or interaction.  Think of it as a script for the chatbot to guide the user through a particular process, like booking an appointment or resolving a technical issue.

• Transfer :

This functionality allows the chatbot to seamlessly connect a user with a live agent when the conversation requires human intervention.  A smooth transfer process ensures the user doesn’t have to repeat information and maintains a positive user experience.

• Typing Delay :

This is a feature that simulates human typing behavior by adding a slight delay between the chatbot’s responses.  This can make the interaction feel more natural and less robotic.

• Voice User Interface (VUI) :

 Similar to CUI, VUI refers to the way users interact with a chatbot through voice commands.  VUIs are becoming increasingly common in virtual assistants and smart speaker devices.

• Webhooks :

These are real-time messaging tools that enable web applications to communicate with external services,  including chatbots.  Webhooks can be used to trigger actions within the chatbot based on events happening on a website or other platform.

• Dialogflow :

This is a Google Cloud Platform service for building conversational interfaces.  Dialogflow provides tools for designing chatbots, including intent recognition, entity extraction, and response generation.  It’s one of many platforms available for chatbot development.

• Voice Assistants :

These are virtual assistants like Amazon Alexa, Google Assistant, or Apple Siri that are primarily controlled by voice commands.  Voice assistants often leverage chatbot technology to understand user requests& provide responses.

• Multimodal Chatbots :

These chatbots can interact with users through a combination of different channels, such as text, voice, and even video.  This allows for a more flexible and natural user experience.