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Further, it can show a list of possible actions from which the user can select the option that aligns with their needs. When the AI-powered chatbot is unsure of what a person is asking and finds more than one action that could fulfill a request, it can ask clarifying questions.

With AI and natural language understanding (NLU) capabilities, the AI bot can quickly detect all relevant contextual information shared by the user, allowing the conversation to progress more smoothly and conversationally. While the rules-based chatbot’s conversational flow only supports predefined questions and answer options, AI chatbots can understand user’s questions, no matter how they’re phrased. In some cases, transfer to a human agent isn’t enabled, causing the chatbot to act as a gatekeeper and further frustrating the user. When the chatbot can’t understand the user’s request, it misses important details and asks the user to repeat information that was already shared. This results in a frustrating user experience and often leads the chatbot to transfer the user to a live support agent. These chatbots struggle to answer questions that haven’t been predicted by the conversation designer, as their output is dependent on the pre-written content programmed by the chatbot’s developers.īecause it’s impossible for the conversation designer to predict and pre-program the chatbot for all types of user queries, the limited, rules-based chatbots often gets stuck because they can’t grasp the user’s request.

However, like the rigid, menu-based chatbots, these chatbots fall short when faced with complex queries. Operating on basic keyword detection, these kinds of chatbots are relatively easy to train and work well when asked pre-defined questions. The rule-based bots essentially act as interactive FAQs where a conversation designer programs predefined combinations of question-and-answer options so the chatbot can understand the user’s input and respond accurately.

Rules-based chatbotsīuilding upon the menu-based chatbot’s simple decision tree functionality, the rules-based chatbot employs conditional if/then logic to develop conversation automation flows.

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Second, if a user’s need is not included as a menu option, the chatbot will be useless since this chatbot doesn’t offer a free text input field. First, this kind of chatbot may take longer to understand the customers’ needs, especially if the user must go through several iterations of menu buttons before narrowing down to the final option. Essentially, these chatbots operate like a decision tree.Īlthough these chatbots offer simple functionality and can be helpful for answering users’ repetitive, straight-forward questions, these chatbots may struggle when faced with more nuanced requests because they are limited to pre-defined answer options. Depending on what the user clicks on, the simple chatbot may prompt another set of options for the user to choose until reaching the most suitable, specific option. Menu-based or button-based chatbots are the most basic kind of chatbot where users can interact with them by clicking on the button option from a scripted menu that best represents their needs. Read more about conversational AI What are the different types of chatbot? 1. However, more advanced chatbots can leverage artificial intelligence (AI) and natural language processing (NLP) to understand a user’s input and navigate complex human conversations with ease. As you’ll discover below, some chatbots are rudimentary, presenting simple menu options for users to click on. Chatbots explainedĪ chatbot is a conversational tool that seeks to understand customer queries and respond automatically, simulating written or spoken human conversations. Before addressing these questions, we’ll start with the basics.

In this blog, we’ll touch on different types of chatbots with various degrees of technological sophistication and discuss which makes the most sense for your business. You may have interacted with these chatbots via SMS text messaging, social media or with messenger applications in the workplace.Ĭhatbots have made our lives easier by providing timely answers to our questions without the hassle of waiting to speak with a human agent. Many of us have interacted with these chatbots or virtual assistants on our phones or through devices in our homes-such as Apple’s Siri, Amazon Alexa and Google Assistant. Now, more than ever, different types of chatbot technology plays an increasingly prevalent role in our lives, from how we receive customer support or decide to purchase a product to how we handle our routine tasks.

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