8 Types of Chatbots Explained: Pick the Best One for Your Business

According to Grand View Research, the chatbot industry is expected to boast a market size of around $27.3 billion by 2030. Furthermore, with 90% of customers interacting with chatbots, it’s a huge business opportunity to tap into.

Nevertheless, chatbots are a boon for every business. The modern day chatbots go beyond simply answering FAQs and are actually interacting with customers and generating leads. With the new advancements of chatbots, it becomes extremely crucial to stay on the basic types of chatbots as a business owner or manager. It helps you decide the right type of chatbot suited to your needs and requirements. Without any delay, let’s get started on types of chatbots!

Breaking down the types of chatbots

What makes chatbots a key business asset is that they serve different purposes. Chatbots, in general, are of various types, and each one of them is designed for specific tasks. This detailed guide underneath will help you understand some common types of chatbots along with the specific purpose they serve.

1. Menu-based chatbots

What is it?: They are the simplest type of chatbots that interact with users through some options thus providing them pre-designed or scripted answers. Pretty much like automated phone menus, they operate like decision trees and run in an easy-to-follow manner; that’s why it’s used to complete simple tasks.

Used for: Menu or button-based chatbots are ideally for FAQs, surveys, and feedback. However, businesses can also utilize these bots for appointment scheduling, checking points, balancing, or displaying simple menus.

Example: The Domino’s Facebook chatbot, Dom, allows users to order their pizza right from messenger while exploring the full menu. All the user needs to do for ordering is choose their desired option and reply to the chatbot’s quest.

Advantages:

• They are straightforward, easy to create and use and are much more accessible as users can navigate the options without typing.
• Such bots can handle simple and repetitive tasks easily.

Limitations:

• As they work like decision trees, they aren't capable of handling complex user queries, which require contextual understanding. Furthermore, if a user's query isn't listed in the set of options, the bot doesn't prove to be helpful.
• Such bots take time to understand the user's specific query while guiding them through menu buttons to reach the final option.

2. Rule-based chatbots

What is it?: Also known as linguistic-based chatbots, they operate on decision trees but have a slightly different logic, i.e., if/but logic, where specific triggers (such as keywords or user actions) lead to specific responses or actions by the chatbot. They are dependent on the keywords and phrases fed to them and provide pre-determined responses based on the keywords identified.

Used for: Pretty much like the above-mentioned ones, keyword recognition-based chatbots are also used for customer support, FAQ assistance, appointment scheduling, etc. Sometimes, they are also used for answering common product enquiries.

Example: The Mya chatbot, makes the recruitment process more efficient by engaging in natural conversations with the candidates and collecting essential information from them. By asking them some specific common questions of the hiring team, it reduces the burden over them. From initial screening to booking and managing appointments, it handles everything.

Advantages:

• Keyword recognition-based chatbots are efficient in providing consistent responses to common user inputs.
• They are time and resource-friendly this allowing human agents to cater to complex user requests.

Limitations:

• Such chatbots, based on keyword identification, fail to identify and understand user context and intent. They too fail to address user inputs beyond their keyword knowledge base.
• Maintaining and scaling up with these bots requires updating their knowledge base, which may sound tiresome.

3. Keyword recognition-based chatbots

What is it?: As the name suggests, such chatbots operate by identifying and analyzing a set of keywords within the user’s input. They scan the user’s input for some specific keywords which trigger a specific response from them.

They are dependent on the keywords and phrases fed to them and provide pre-determined responses based on the keywords identified.

Used for: Pretty much like the above-mentioned ones, keyword recognition-based chatbots are also used for customer support, FAQ assistance, appointment scheduling, etc. Sometimes, they are also used for answering common product enquiries.

Example: The Mya chatbot, makes the recruitment process more efficient by engaging in natural conversations with the candidates and collecting essential information from them. By asking them some specific common questions of the hiring team, it reduces the burden over them. From initial screening to booking and managing appointments, it handles everything.

Advantages:

• Keyword recognition-based chatbots are efficient in providing consistent responses to common user inputs.
• They are time and resource-friendly this allowing human agents to cater to complex user requests.

Limitations:

• Such chatbots, based on keyword identification, fail to identify and understand user context and intent. They too fail to address user inputs beyond their keyword knowledge base.
• Maintaining and scaling up with these bots requires updating their knowledge base, which may sound tiresome.

4. AI-powered chatbots

What is it?: AI-powered chatbots are one of the most technologically advanced chatbots which can provide intelligent human-like response to user inputs. Powered by AI, ML, NLP and such advanced analytics, these chatbots are highly efficient in understanding user intent.

AI-powered chatbots have the ability of entity recognition extracting specific information from users’ messages and providing personalization and context understanding. For instance, if a customer orders a product from an ecommerce store, the AI chatbot of the ecommerce store will recognize the customer in future orders, greet, provide recommendations, and personalize.

These chatbots are intelligent enough to handle any level of complexity in conversation but are sensible enough to hold the conversation whenever a human agent is required.

Used for: From basic tasks like collecting user data and preferences to upselling, cross-selling and identifying and nurturing qualified leads, AI-powered chatbots can do a variety of tasks. They can provide personalized and customized support to users wherever necessary.

Example: HDFC Bank’s EVA (Electronic Virtual Assistant) is an AI-powered chatbot that handles over 2.7 million customer queries within 6 months. EVA provides instant responses to a range of banking inquiries, significantly reducing the workload on human agents and improving customer service efficiency.

Advantages:

• Due to their conversational nature, they can identify user’s pain points, intent and context better thus improving customer satisfaction.
• They go beyond conversations, can self-learn, and are contextually intelligent.
• They specialise in many simple and complicated tasks.

Limitations:

• While they offer personalised experience, sometimes the lack of human touch is evident.
• Maintaining user privacy is crucial while ensuring multilingual support.

5. Hybrid chatbots

What is it? Hybrid chatbots are the ones that have the capabilities of both a rule-based & AI-powered one. Such chatbots are multifunctional - they answer basic queries according to rule-based systems and use the AI-powered system to understand and answer complex queries.

Hybrid chatbots have the predictive and reliability factors of a rule-based chatbot with additional support of AI-driven learning capabilities. The best part about Hybrid chatbots is that they allow live chat use simultaneously, meaning a human agent can take over the conversation anytime.

Used for: From making customer service more personalised to helping customers buy their favorite product, hybrid chatbots serve a variety of purposes. They are capable of automating a huge chunk of business operations.

Example: The US National Railway service has a hybrid chatbot named Amtrak’s Julie Virtual Assistant that attends to users’ queries. While the bot uses rule-based mechanisms for answering basic questions like train schedules, it also uses AI/ML capabilities to answer complex user queries.

Advantages:

• They are versatile, efficient, multifunctional, and serve various purposes, and their scope is unlimited.
• As they work on both rule-based and AI mechanism, such bots are conversational in nature and deliver seamless customer experience.
• Hybrid chatbots can actually engage in natural, human-like conversations while understanding the intent, entity and context of users. Additionally, they also have well-defined fallback mechanisms.

Limitations:

• While such bots are conversational, they are dependent on gradual learning to improve their understanding of user intent.
• They are technologically advanced and complex too.
• As they learn from user conversations which may have user data, privacy concerns may also come up

6. Voice chatbots

What is it?: A voice chatbot is a voice-activated assistant that runs under various powerful AI technologies. These chatbots leverage natural language processing (NLP, speech recognition and respond to a conversational tone. These chatbots understand and respond to voice commands, which provides a hands-free interaction.

Used for: Voice chatbots can assist users with tasks like scheduling meetings and setting reminders as virtual assistants. Additionally, e-commerce platforms use voice chatbots to do voice searches.

Example: A common example of these kinds of voice chatbots is Amazon Alexa, which is integrated into Amazon’s smart devices, allowing users to control smart home features, shop online, and get information using voice commands. Similarly, Google Assistant is found on Android devices and Apple Siri on iOS devices.

Advantages:

• Voice chatbots allow users to interact without needing to type.
• They provide an accessible interface for users who may have difficulty using traditional text-based systems like those with visual impairments.

Limitations:

• These chatbots may struggle to accurately recognize and interpret user accents, regional dialects, or non-native speakers.
• The chatbot may find it difficult to understand user queries in background noise and variations in speech.

7. Generative AI chatbots

What is it?: Generative AI chatbots are some of the advanced versions of AI bots. These are sophisticated evolutions capable of creating new and contextually relevant responses. Generative AI chatbots mostly use large-scale neural networks such as transformer models like GPT-4. It can adapt to the user’s conversation style and mold the information per their intent.

These chatbots became limitless when generating content, and along with great text information, they can also produce high-quality images and voice. These chatbots can be analytic, predictive, logical, and creative too.

Used for: Generative chatbots are widely used in customer service, virtual assistants, content creation, education, and entertainment. They help automate responses, provide personalized interactions, generate creative content, and assist with learning.

Example: Open AI’s ChatGPT, also known as “do-anything-machine,” can process almost all user requests while being capable of summarising texts and providing visual descriptions. It’s multimodal and assists every Internet user almost every day in all possible ways.

Advantages:

• Generative AI chatbots tailor responses based on individual user preferences and history, creating a more engaging and customized experience.
• Such chatbots can handle multiple conversations simultaneously, making it cost-effective and easy to scale customer support during peak times.
• These chatbots can also generate diverse and creative content.

Limitations:

• While these chatbots excel at understanding user intent, they struggle with maintaining it in long conversations.
• Besides [chatbot security](https://www.thinkstack.ai/blog/chatbot-security/) risks, they may, at times, provide biased or factually incorrect information unintentionally due to the data they were trained on.

8. NLP chatbots

What is it?: NLP chatbots are those that focus on understanding and processing human language and mimicking human conversation. What makes them different from generative AI chatbots is that while generative AI chatbots emphasize creation, NLP chatbots are more about comprehending human language and interactions.

Used for: NLP chatbots are used in all industries and are more conversational in nature. From conversational commerce in marketing to patient counseling in healthcare and onboarding new employees in HR, they serve a variety of purposes.

Example: Disney developed a chatbot using NLP technology that allows users to interact with Officer Judy Hopps, a character from the hit 2016 movie Zootopia. Through this chatbot, users can engage in conversations with Judy as she seeks assistance in solving various crimes.

Advantages:

• Generative AI chatbots tailor responses based on individual user preferences and history, creating a more engaging and customized experience.
• Such chatbots can handle multiple conversations simultaneously, making it cost-effective and easy to scale customer support during peak times.
• These chatbots can also generate diverse and creative content.

Limitations:

• One limitation of NLP chatbots is their difficulty in understanding nuanced language, such as sarcasm, idioms, or cultural references. This can lead to misinterpretations, where the chatbot provides responses that are irrelevant or inappropriate.

Ruled based chatbots vs. AI-powered chatbots

How to choose the right type of chatbot for your business?

After exploring the various types of chatbots, it’s clear that they offer a wide range of possibilities and features. However, understanding these options alone is not enough to determine the right chatbot for your business. Not every chatbot will be a perfect fit. It’s crucial to choose one that aligns with your business objectives and offers the necessary features and support. To help you make the right decision, consider the following factors:

1. Purpose and use case

Figure out the list of tasks and roles you want your chatbot to perform. Decide specific use cases and specialties required, as your chatbot must be tailored to perform it. Make sure it is capable enough to handle large volumes and has efficiency in handling operation and customer service.

2. Ease of use

Select a chatbot that can easily integrate with your existing system and follow a straightforward method of deployment. Platforms like Thinkstack for a chatbot offer solutions by enabling zero-code chatbot building and implementation. With Thinkstack, you can integrate an advanced AI-powered chatbot into your store with just a few clicks, making the process accessible and user-friendly.

3. Required features

Ensure your chatbot has all of these required features:

• Natural Language Processing (NLP): Ensure chatbots have NLP capabilities, which allows chatbots to understand and respond to user queries effectively.
• Multilingual Support: If your business deals with a global audience then your chatbot must be able to converse in multiple languages to ensure better communication and customer satisfaction.
• AI and Machine Learning: Ensure the chatbot has AI and ML capabilities that help the chatbot learn from interactions to improve its responses over time. AI-powered chatbots also have better data processing and information-gathering capabilities.
• Integration and API availability: Choose a chatbot that supports omnichannel integration independently. This can effortlessly integrate with social media platforms, CRM, ERO, ecommerce platforms and more. Additionally, ensure it offers APIs that seamlessly integrate with your business applications.
• Customization: Opt for a chatbot that offers broad customisation options, from tailoring its behavior, appearance, and conversational style to matching your brand.
• Analytics and reporting: A chatbot with advanced analytics and reporting that can show you details about performance, user engagement and areas of improvement. Ensure the chatbot has real-time tracking and a diverse layer of information.

4. Scalability

Consider whether the chatbot can handle your expected volume of interactions as your business grows. It must retain its efficiency in high workload and can seamlessly scale. Security and compliance Ensure your chatbot adheres to security practices and all the industry-specific protocols. It must include data encryption and security authentication methods.

5. Budget

Set a realistic budget for your chatbot project; the budget should align with your requirements for the chatbot. Compare different chatbot services and consider the platform’s pricing, deployment options, and potential scalability needs for the final selection.

Summing Up!

The advancement of chatbot technology has now introduced six distinct types. However, as technology continues to evolve, we can expect the emergence of more advanced subcategories and innovations.

Despite this, the current chatbot types are already well-equipped to meet nearly all business requirements. If you’re skeptical or unsure where to start, don’t hesitate to contact our team for guidance right now!