Rule-Based Chatbots vs. AI Chatbots: Key Differences

June 22, 2020 (Updated)

Conversational Messaging

Chatbot success stories continue to inspire many businesses to adopt a bot of their own. But, they’re not always sure which type of chatbot to choose. Let’s look at rule-based chatbots vs AI chatbots, and which one is right for your company.

What are rule-based chatbots?‍

Rule-based chatbots are also referred to as decision-tree bots. As the name suggests, they use a series of defined rules. These rules are the basis for the types of problems the chatbot is familiar with and can deliver solutions for.

Like a flowchart, rule-based chatbots map out conversations. They do this in anticipation of what a customer might ask, and how the chatbot should respond.

Rule-based chatbots can use very simple or complicated rules. They can’t, however, answer any questions outside of the defined rules. These chatbots do not learn through interactions. Also, they only perform and work with the scenarios you train them for.

What are AI chatbots?‍

In comparison, AI chatbots that use machine learning understand the context and intent of a question before formulating a response.

These chatbots generate their own answers to more complicated questions using natural-language responses. The more you use and train these bots, the more they learn and the better they operate with the user.

Advantages of a rule-based chatbot

While rule-based bots have a less flexible conversational flow, these guard rails are also an advantage. You can better guarantee the experience they will deliver, whereas chatbots that rely on machine learning are a bit less predictable.

Some other advantages of a rule-based chatbot are that they:

  • are generally faster to train (less expensive)
  • integrate easily with legacy systems
  • streamline the handover to a human agent
  • are highly accountable and secure
  • can include interactive elements and media
  • are not restricted to text interactions

Advantages of AI chatbots

Many people view AI Bots as a more sophisticated cousin of chatbots. They work well for companies that will have a lot of data. Although they take longer to train initially, AI chatbots save a lot of time in the long run.

AI chatbots:

  • learn from information gathered
  • continuously improve as more data comes in
  • understand patterns of behaviour
  • have a broader range of decision-making skills
  • can understand many languages

Which chatbot is right for your business?

While AI chatbots are more advanced, they’re not always necessary. For smaller companies or those with specific goals, rule-based chatbots are a more appropriate solution. Companies that fall into the categories below should consider a rule-based chatbot:

  • You know the goal you’re leading people towards
  • You’re interested in using a chatbot as an FAQ resource
  • Your chatbot will funnel users to human agents
  • You don’t have a ton of example conversations to feed it

Do rule-based chatbots rule?

People appreciate the transparency of what a chatbot can and can’t do. When the conversation is wide open, people often don’t start it. By providing buttons and a clear pathway for the customer, things tend to run more smoothly.

AI chatbots do have their place, but more often than not, our clients find that rule-based bots are flexible enough to handle their use cases. Of course, the more you train your rule-based chatbot, the more flexible it will become.

Questions that your rule-based chatbot can’t answer represent an opportunity for your company to learn. You can easily tweak and modify the rules, whereas machine learning is more difficult to course-correct when things go wrong.

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