Types of chatbots
Businesses worldwide have become increasingly reliant on chatbots to enhance customer engagement, optimize internal processes, and expedite support services. These automated conversation tools that can respond to user queries, assist with tasks, and handle data collection — plus, with integration available into websites, messaging platforms, and voice assistants, they essentially function as a 24/7 virtual support team.
It’s not surprising then, that the global chatbot market size is expected to reach $27.29 billion by 2030 — that’s a 23.3 percent growth rate from 2025 to 2030. But despite their popularity, there’s no one-size-fits-all chatbot. Each type has unique capabilities and limitations, so it’s crucial to understand these different chatbots before committing to one.
In this article, we’ll look at seven types of chatbots to help you pinpoint the best fit for your organization’s needs:
- Menu-based chatbots
- Rule-based chatbots
- AI-powered chatbots
- Voice chatbots
- Generative AI chatbots
- Keyword-based chatbots
- Hybrid chatbots
By understanding the strengths and weaknesses of each of these types of chatbots, you’ll be in a better position to select the right fit to match your goals, budget, and technical resources.
What are chatbots and why do they matter?
Chatbots are computer programs designed to simulate conversation and automate interactions, allowing you to
- Free up human resources by letting AI handle repetitive tasks, such as answering frequently asked questions or assisting with simple troubleshooting.
- Scale your customer service capabilities without drastically increasing headcount.
- Enhance user experiences by offering a personalized journey, guiding people through complex processes, and providing relevant incentives where necessary.
Choosing a type of chatbot that aligns with your business objectives is key to tapping into these benefits.
How to choose the right chatbot for your business
Choosing the best chatbot model ultimately comes down to your business’s unique requirements, budget, and technical know-how. A menu-based or keyword-based chatbot might serve you well if you mainly deal with predictable inquiries. Rule-based systems can be helpful for organizations in strictly regulated fields, offering reliability and compliance. AI-powered or generative AI chatbots work best for those aiming for more nuanced, human-like interactions as long as they have the data (and budget) to support advanced machine learning.
But you should also consider your user base. A voice chatbot is ideal if your customers are frequently on the go or have accessibility needs. Meanwhile, a hybrid approach can significantly give you the best of both worlds if your business has varied or growing demands.
Ask yourself the following questions before making a decision:
- What is my main objective? Perhaps it’s customer service, lead generation, e-commerce, or something else.
- Do I have enough data and expertise to train an AI-powered solution?
- How critical is personalization and conversational nuance?
- Is there a strict set of industry regulations or compliance measures I must follow?
With these answers in mind, you’ll be better placed to choose from one of the following seven types of chatbots.
1. Menu-based chatbots
Menu-based chatbots rely on structured decision-tree flows to guide users through menus or predefined options. They are the digital equivalent of an automated phone tree, where users press specific keys to access different services.
In practice, a menu-based chatbot might present multiple buttons or prompts — for instance, “Billing,” “Technical Support,” or “Feedback.” The user picks a category, and the bot offers the following options. This continues until the conversation reaches its logical conclusion. Typically, these chatbots are straightforward to implement and work well when your business needs to handle a narrow range of simple requests.
Best for: Simple FAQ handling, surveys or quizzes, lead qualification forms that ask basic questions (like name, company, and budget range).
| Benefits | Limitations |
|---|---|
| Simple to create and implement | Has a rigid structure |
| Don’t require complex coding or artificial intelligence | Struggle to respond effectively to questions outside their predefined options |
| Very user-friendly with a highly predictable conversation flow | |
| Effective for businesses dealing with a small number of specific queries |
2. Rule-based chatbots
Rule-based chatbots — sometimes called trigger-based or “if-then” chatbots — operate on carefully crafted logic. Designers set specific conditions that cause the bot to respond in a particular way. For example, if the user’s message contains the phrase “order status,” the chatbot automatically provides a link to track the package or prompts the user for more details.
Unlike menu-based bots that rely on structured decision trees, rule-based chatbots look for certain triggers in user inputs. These triggers can be keywords, phrases, or data points like location.
Best for: Technical troubleshooting and companies that deal with repetitive, predictable scenarios.
| Benefits | Limitations |
|---|---|
| Reliable, consistent, and accurate when a conversation follows predefined rules | If an inquiry doesn’t match existing conditions, the chatbot can become confused |
| Large rule libraries can be time-consuming to maintain as your product lineup or knowledge base grows |
3. AI-powered chatbots
AI-powered chatbots are a step above rule-based systems. Rather than relying solely on triggers, these bots use machine learning and natural language processing (NLP) to interpret user intent dynamically. By analyzing patterns in large training data sets, they learn how to respond with increasing accuracy over time.
These chatbots excel at understanding complex or ambiguous user inputs. For instance, if a customer writes, “Hey, my invoice seems incorrect. Can you help?” An AI-powered bot can interpret that “invoice” and “incorrect” likely indicate a billing query and then reply with the correct next steps or escalation path.
Best for: Customer support, personalized shopping assistants, and healthcare inquiries.
| Benefits | Limitations |
|---|---|
| Versatile and adaptive to customer needs | Require effective training and technical expertise to maintain |
| Can provide 24/7 customer support, reducing wait times and improving customer satisfaction | Maintenance and development costs can be higher than other chatbots |
| Provide personalized customer experiences, like offering specific discounts or recommendations | |
| Long-term investment for deeper, more human-like interactions |
4. Voice chatbots
Voice chatbots are an evolution from text-based chatbots. These bots are integrated into popular virtual assistants like Amazon’s Alexa, Google Assistant, or Apple’s Siri, enabling users to interact through spoken language rather than typed messages. Their technology combines speech recognition, natural language understanding, and text-to-speech to deliver a hands-free interaction.
Best for: On-the-go users, phone-based customer support systems, customers with accessibility needs.
| Benefits | Limitations |
|---|---|
| More convenient than text-based chatbots, particularly for users who may be driving or cooking | Struggle with accents, background noise, or users speaking quickly |
| Provide quicker interactions and improved accessibility, particularly for individuals with visual or mobility impairments | Longer, more nuanced speech can confuse the system if it’s not designed for open-ended queries |
| Capabilities are growing with increasing popularity across industries |
5. Generative AI chatbots
Generative AI chatbots are at the cutting edge of conversational technology. Rather than relying on predefined rules or mapped responses, they use advanced language models — often called Large Language Models — to generate new text in real-time. These bots analyze enormous amounts of textual data to create human-like responses, drawing from context, grammar structures, and semantic relationships learned during training.
Best for: Interactive customer support, creative content generation, and training simulations.
| Benefits | Limitations |
|---|---|
| Can handle broader, more free-flowing conversations | May produce off-topic or factually incorrect responses if not guided properly |
| Can recall earlier parts of the conversation, making interactions feel more fluid and “human” | Guardrails or fine-tuning with specific data sets may be needed to ensure reliability |
| Offer unmatched flexibility, rapidly advancing accuracy, and contextual understanding | Can be affected by potential bias if training data skews in certain directions |
6. Keyword-based chatbots
Keyword-based chatbots resemble rule-based bots but focus more explicitly on recognizing keywords in user messages. For example, a chatbot might be programmed to respond with shipping information whenever it spots the word “shipping.” This approach can be particularly straightforward for smaller operations looking to automate responses to frequently asked questions.
Best for: Answering repetitive questions, handling basic inquiries.
| Benefits | Limitations |
|---|---|
| Extremely simple to set up using a handful of keywords related to common queries (like pricing, refund, or store hours) | Don’t truly understand context, so are more likely to misfire if a message contains multiple keywords |
| Very user-friendly | Spelling mistakes, unusual phrasing, and synonyms can throw them off |
| Require a robust keyword library with variations to account for different wording |
7. Hybrid chatbots
Hybrid chatbots combine elements from multiple types of chatbots to deliver a more versatile solution. Businesses often blend rule-based logic with AI capabilities, creating a system that can handle straightforward queries via defined triggers, but shifts to an AI-powered approach for more complex questions.
Best for: Managing a wide range of inquiries with both structured and flexible responses.
| Benefits | Limitations |
|---|---|
| Can deal with open-ended and unpredictable questions | Set up and maintenance can be more complex and expensive |
| Evolve with your business — for example, you might begin by heavily relying on rules and triggers, then gradually add AI functionality as you collect more data or need more sophisticated features |
Build your chatbot in minutes with Jotform
When you’re ready to implement a chatbot, Jotform’s AI Chatbot Builder simplifies the process from start to finish — letting you create custom chatbots in just a few clicks. Its user-friendly interface means you don’t need extensive coding experience to get set up, and with a variety of configurations, you can choose whether you want a simple keyword-based system or a more advanced AI-driven approach.
But that’s not all. With Jotform, you can
- Customize the chatbot’s appearance and conversation flow to reflect your brand and objectives.
- Expand your chatbot’s knowledge base by entering information manually, adding links, uploading documents, or creating question-and-answer pairs.
- Enhance your e-commerce site with Jotform’s e-commerce AI chatbot to handle customer inquiries and product recommendations and even help you generate leads.
- Choose from a range of ready-to-use chatbot templates for various industries, so you can hit the ground running without building every conversation from scratch.
Jotform is designed to grow with your business, so there’s no need to go back to the drawing board if you decide you want more AI capabilities later on. And the best part? You can start creating for free today.
Photo by Christin Hume on Unsplash
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