Rule-Based Chatbots: Examples & Possible Applications

About this guide

In the age of digitization, customers expect a quick and effective solution to their concerns. Companies are therefore increasingly using chatbots to improve customer service. Rule-based chatbots offer a simple solution to answer customer inquiries. In this article, we will take a closer look at what exactly is behind it, which areas of application are best suited and which advantages and disadvantages of rule-based chatbots have compared to AI-based chatbots.

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Definition: What Is a Rule-Based Chatbot?

Rule-based chatbots are computer-based dialog systemsthat can communicate with people in real time. They respond to questions by drawing on predefined rules and decisions. They recognize the user's intent by scanning the inputs for specific keywords. They then provide prescribed answers from a database that contains most suitable keywords or similar patterns. This means that they can only respond to predictable questions and phrases that have been defined in advance by the developers. In addition, some rule-based chatbots don't even allow free text to be entered, but offer buttons and so-called click strings through which a user can click.

Rule-based chatbots are as dialog tree structured. The aim is to simulate the back and forth of a real conversation. However, your conversations are limited to a specific topic.

Contrary to others chatbot systems They are less flexible but easier to program.

What Are the Possible Applications?

Rule-based chatbots are used in various areas, for example:

  1. customer service: Rule-based chatbots can quickly process customer inquiries by answering frequently asked questions and helping solve problems. They can also take on routine tasks such as managing orders or changing delivery details.
  2. ecommerce: General questions about order status or return conditions can be answered by rule-based chatbots be answered.
  3. healthcare: Rule-based chatbots can help patients make appointments, submit lab results, or answer questions about symptoms. They can also help manage health records and monitor medication intake.
  4. Travel and tourism industry: Rule-based chatbots are able to help travelers book flights, hotels, and rental cars — or plan trips and activities. They can also provide information on travel destinations and travel conditions.

Examples of Rule-Based Chatbots

You may encounter rule-based chatbots more often than you think. This is what they may look like in practice:

Lego Chatbot Sophia

The manufacturer of the colorful building blocks uses a rule-based chatbot to assist with topics related to your own order, product complaints or the LEGO account.

HelloFresh virtual assistant

With HelloFresh's virtual assistant, you can change your subscription, clarify questions about billing and payment, or even report ingredient errors.

Zurich airport chatbot

Zurich Airport's messaging assistant helps travelers find their way around the airport and provides them with important flight information.

Provider of Rule-Based Chatbots

There are now many providers of rule-based chatbots that help companies develop and implement their own chatbots. Here are a few examples:

  • ChatBot: Here, customers can use ready-to-use templates for rule-based chatbots.
  • Airport AI: A provider specifically for airport chatbots, which should ensure that passengers have a better experience at the airport and can quickly resolve their concerns and questions.
  • Chatfuel: This software provides a kit for rule-based chatbots that can be connected to Facebook, Instagram or other messengers.
  • ManyChat: A chatbot builder that enables the development of rule-based chatbots without programming knowledge. ManyChat offers integrations with various platforms such as Facebook Messenger, Instagram, and WhatsApp.
  • LINK Mobility: A provider of rule-based chatbots that handle frequent customer inquiries in marketing and ecommerce answer.

Rule-Based vs. AI-Based Chatbots

Not all chatbots are the same! There are various forms of this. The two most common types are rule-based chatbots and AI-based chatbots. As we explained at the beginning, rule-based chatbots are pre-programmed to answer specific questions or inquiries from users. AI-based chatbots, on the other hand, use artificial intelligence to interact with users naturally using machine learning and natural language processing.

Sounds complicated? Let's look for an example from the offline world: Rule-based chatbots are, so to speak, a standard dance in which every step is defined in advance. In contrast, AI-based chatbots are like improvisational dancers — they can adapt to any situation and are constantly learning new things.

What are the differences exactly? This is shown in the following table:

Rule-Based ChatbotAI Chatbot
Based on predefined rules and decision treesUses artificial intelligence to respond to natural language
Limited ability to handle complex conversationsCan manage complex conversations and provide contextual answers
Requires frequent updates to handle new questions and demandsImproves autonomously through machine learning without constant updates
Cannot predict trends due to limited conversation pathsCan analyze preferences and trends from free-text input and conversations
Quick to implement and cost-effectiveMay be more expensive and time-consuming due to ML models
No wow-effect—serves mainly as a clickable info sourceOften creates wow-effects—answers complex queries, engages in small talk and humor
Cannot answer unknown questions or requestsCan often handle unknown inputs using context and experience
Mostly click-based: users select from predefined optionsOffers both clickable options and free text/speech input
Typically used for simple, repetitive tasks like orders or appointmentsApplicable across various fields: customer service, sales, marketing, HR, and more
Usually no free-text input due to lack of NLPAllows open input—NLP enables understanding of user intent even in long texts

Conclusion

Rule-based chatbots are a type of chatbot that is based on established rules and decisions. They are easy to implement and are suitable for simple, repetitive tasks such as ordering or making appointments.

However, rule-based chatbots have their limitations because they are unable to conduct complex conversations and answer unknown questions. However, they can be useful for specific use cases, particularly when it comes to providing quick and cost-effective solutions to implementing. But if you're looking for a chatbot that answers complex questions and has more natural conversations, you should consider an AI-based chatbot. With AI-based chatbots, you can achieve a higher customer satisfaction reach out and provide more efficient support.

Want to Try Out an AI Chatbot?

Have you become curious? If you also want to create your own chatbot for your company, then let's go! With our tool, you can easily try it out for yourself:

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