Different Types of Chatbots: Find the Best Virtual Assistant for your Business

Chatbots are the future of all virtual interactions. They have grown in popularity as a way of communication between businesses and their customers. The Global Chatbot Market was valued at $2.6 billion in 2019 and is increasing at a compound annual growth rate of 29.7% and is expected to reach $9.4 billion in 2024.

What is Chatbots?

Chatbots are mainly used in customer support conversations to automate and burden off simple tasks from human customer service agents. These artificial intelligence-powered tools are designed to mimic human conversation and assist in various contexts.

Learn more about What is Chatbot

Types of Chatbots

Not all chatbots are created equal; there are several types of chatbots. Understanding the differences between these chatbots can help businesses choose the right one for their needs and ensure that their customers have a positive experience. In this blog, we’ll explore the various types of chatbots and what makes each one unique.

There are three types of chatbots based on their technology and use cases.

1. Simple Chatbots (or rule-based chatbots)
2. Smart Chatbots (or AI-powered chatbots)
3. Hybrid Chatbots (or a combination of rule-based and AI-powered chatbots)

What are the Different Types of Chatbots and Their Features

Basic Chatbots

Basic chatbots are the most simple chatbots. They are called rule-based chatbots because they operate on a fixed set of rules to understand and respond to user input. The rules can be simple or complex, and the chatbot’s responses are limited to what is pre-programmed into it.

Pros

• Easy to develop and implement
• Inexpensive to maintain
• Provides consistent responses

Cons

• Limited functionality
• Not able to handle complex or unanticipated user queries
• User or customer experience may suffer if the chat bot is unable to answer the user’s question

Use cases

Rule-based chatbots are typically used for simple tasks such as answering FAQs, providing basic customer support, or routing inquiries to the appropriate department.

• Customer service: Rule-based chatbots are commonly used to help customers find the information they need and troubleshoot problems. For example, a rule-based chatbot for a telecom company could help customers with billing queries, service outages, or technical issues.
• FAQ bots: Rule-based chatbots can be designed to answer frequently asked questions (FAQs) about a product, service, or organization. These bots can help save human customer service representatives time by handling simple queries and providing customers with instant responses.
• Booking and reservation bots: Rule-based chatbot types can book appointments, reservations, or tickets. For example, a restaurant could use a chatbot to help customers reserve a table, or a hotel could use a chatbot to help customers book a room.
• Personal finance: can be used to help users with budgeting, investing, and financial planning. For example, a chat bot could help users set up a budget and track their spending.
• Education: Rule-based chatbots can be used in education to help students with homework, answer questions about a subject, or provide study resources. For example, a chatbot could help students practice math problems, learn a new language, or prepare for tests.
• HR bots: can be used in Human Resources to help employees with queries related to employee benefits, company policies, and procedures. For example, an employee could use a chatbot to ask for a day off, check their sick leave balance, or learn about the company’s code of conduct.

Also Read: Types of Agents in AI

What is a Smart Chatbot?

AI-powered chatbots, known as natural language processing (NLP), use machine learning algorithms to understand and interpret natural language. Unlike rule-based chatbots, AI-powered chatbots can learn and adapt to new situations and handle a broader range of user inquiries. AI-powered chatbots can be further categorized into three types of AI Chatbots: Machine Learning (ML) chatbots, Deep Learning (DL) chatbots, and Natural Language Understanding (NLU) chatbots.

Pros

• Can handle complex and unanticipated user queries
• Provide more personalized responses
• Can learn and adapt to new situations

Cons

• More complex and expensive to develop and maintain
• May require extensive training data to work effectively
• Can be difficult to implement across multiple languages

Developments of AI-powered chatbots

• Machine Learning (ML) chatbots: use machine learning (ML) and Artificial Intelligence (AI) algorithms to learn from user data and improve over time. They can handle various user inquiries and adapt to new situations.
• Deep Learning (DL) chatbots: These bots use deep learning algorithms to learn from large amounts of user data and can handle complex user inquiries. They are also able to recognize patterns and predict user intent.
• Natural Language Understanding (NLU): These AI bots use advanced language processing algorithms to understand user intent and context. They can handle complex queries and provide more personalized responses.

Use Cases

• Customer Service: Customer support chatbots empowered with AI can handle customer inquiries, complaints, and support requests in real time, providing a quick and efficient way for customers to get the help they need.
• E-commerce: can help customers find products, place orders, and get support for post-sales issues, such as returns or refunds.
• Healthcare: can help patients book appointments, receive medical advice, and access basic healthcare information.
• Finance: These types of chatbots can help customers with banking transactions, such as checking account balances, transferring money, and paying bills.
• Education: Chatbots can assist students with course-related questions, provide personalized learning recommendations, and help educators manage administrative tasks.
• Travel: can help travellers book flights, hotels, and rental cars, as well as provide travel information, such as weather updates and tourist attractions.
• Human Resources: can help employees with common HR tasks, such as updating personal information, requesting time off, and accessing benefits information.

Explore How AI Voice Bots are Helping Telecommunications Industry in Dormant Reactivation

What is a Hybrid Chatbots?

A hybrid chatbot is a combination of rule-based and AI-powered chatbot type. They use pre-programmed rules to handle simple tasks and machine learning algorithms to handle more complex tasks. This allows the chatbot to provide the best of both worlds: consistent responses for simple tasks and personalized responses for complex tasks.

Pros

• Can handle both simple and complex user queries
• Provides consistent responses for simple tasks
• More cost-effective than fully AI-powered chatbots

Cons

• May be more complex to develop and maintain than rule-based chatbots
• May require extensive training data to work effectively

Use cases

Hybrid chatbots combine the benefits of rule-based and AI-powered chatbots, providing an enhanced user experience that seamlessly blends automation with human assistance. Some use cases of hybrid chatbots include:

• Customer Service: Hybrid chatbots can handle common customer queries and requests but can seamlessly transfer customers to human agents when necessary for more complex issues.
• Sales: can help customers find products and make purchases. They can also provide personalized recommendations and connect them with human sales representatives for further assistance.
• Healthcare: can provide patients with basic medical advice and assist with scheduling appointments. They can also connect them with human doctors or nurses for more specialized care.
• Banking: can help customers with basic banking tasks like account balances and transactions. They can also provide personalized financial advice and connect them with human, financial advisors for more complex matters.
• Education: Hybrid chatbots can assist students with basic course-related questions and connect them with human teachers or tutors for more personalized instruction.
• Travel: can provide travellers with basic travel information and booking assistance. They can also connect them with human travel agents for specialized advice and planning.

Rule Based Chatbot vs AI Chatbot

Rule Based Chatbot- A rule-based chatbot adheres to human-written scripts and pre-established rules. It struggles with anything that deviates from these guidelines and can only react in certain ways to certain inquiries. A decision tree might be used to compare it: if you say "X," it will respond with "Y."

AI Chatbot- Like chatbots driven by machine learning, AI chatbots gain knowledge from a tremendous amount of data. With increased involvement, it can comprehend a wider variety of inquiries, offer more adaptable answers, and get better over time. AI chatbots are more versatile and helpful for a variety of jobs since they can manage complex discussions better than rule-based ones.

Learn About the Role of Natural Language Processing in AI-Driven Contact Centers

How are AI Chatbots Different?

AI chatbots stand apart from traditional chatbots due to their natural language processing capabilities, context comprehension, adaptability, and learning. They engage in complex, open-ended discussions, support multiple languages, and offer personalized experiences. Unlike rule-based counterparts, different types of AI chatbots generate responses dynamically, improve through interaction, and mimic human conversational nuances. This advancement signifies a shift from rigid scripted interactions to more human-like, intelligent, and versatile communication tools.

Conclusion

In conclusion, choosing the right type of chatbot depends on your business needs and the tasks you want the chat bot to perform. Rule-based chatbots are best for simple tasks, while AI-powered ones are better suited for more complex tasks. Hybrid chatbots offer the best of both worlds and can be a cost-effective solution for businesses.

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