Types of chatbots

Adspl tech
4 min readJan 18, 2022

A chatbot for an eCommerce website is very different from one for banking. In the same way that individuals differ in their personalities and abilities, bots differ in their look and activity!

In this article, we’ll discuss the many sorts of AI chatbots, as well as the various types of business chatbots, as well as their applications and functionalities. This will help you learn how many different sorts of chatbots there are and which one would be best for your company!

The various varieties of bots are listed below.

1 Chatbots with a menu or buttons

The most basic sort of chatbot now in use is one that is based on a menu or a button. Most of the time, these chatbots are glorified decision tree hierarchies that are displayed to the user as buttons. These chatbots, like the automated phone menus we all deal with on a regular basis, demand the user to make many choices in order to get to the ultimate response.

While these bots are adequate for answering FAQs, which account for 80% of support requests, they fall short in more complicated scenarios where there are too many variables or too much expertise at play to forecast how users should confidently arrive at certain responses. It’s also worth noting that menu/button-based chatbots are the slowest to bring the user to the value they want.

2 Linguistic in nature (Rule-Based bots)

A linguistic chatbot may be the right answer for you if you can anticipate the types of queries your clients will ask. If/then logic is used by linguistic or rules-based chatbots to build conversational flows. You must first establish the language requirements for your chatbots. Conditions can be set to evaluate the words, their order, synonyms, and other factors. If the inbound inquiry meets the conditions set by your chatbot, your clients will receive prompt assistance.

It is, however, your responsibility to verify that each permutation and combination of each question is defined; otherwise, the chatbot would be unable to comprehend your customer’s input. This is why, despite its widespread use, language models can take a long time to evolve. Rigidity and specificity are required by these chatbots.

3 Chatbots that recognize keywords

Keyword recognition-based chatbots, unlike menu-based chatbots, can listen to what users input and answer accordingly. To determine how to offer a suitable response to the user, these chatbots use customizable keywords and an AI application called Natural Language Processing (NLP).

When faced with a large number of similar questions, these types of chatbots fall short. When there are keyword redundancies across numerous linked inquiries, NLP chatbots will start to falter.

They that are a mix of keyword recognition and menu/button-based are becoming increasingly common. If the keyword recognition functionality fails or the user requires assistance in finding an answer, these chatbots give users the option of directly asking their inquiries or via the chatbot’s menu buttons.

4 chatbots that use machine learning

Do you know what a contextual chatbot is? A contextual chatbot is significantly more sophisticated than the previous three bots. Machine Learning (ML) and Artificial Intelligence (AI) are used by these chatbots to recall discussions with specific users in order to learn and evolve over time. Chatbots with contextual awareness, unlike keyword recognition-based bots, are clever enough to self-improve based on what users are asking for and how they are requesting it.

For instance, consider a contextual chatbot that allows users to place food orders; the chatbot will save data from each discussion and learn what the user prefers to order.

As a result, when a user speaks with this chatbot, it will eventually remember their most common order, delivery location, and payment information, and will simply ask whether they’d like to repeat it. Instead of having to react to a series of questions, the user simply needs to say “Yes” and the food will be ready!

While this meal ordering example is simple, it demonstrates how effective conversation context can be when combined with AI and machine learning. Any chatbot’s ultimate goal should be to give a better user experience than the current state of affairs. One of the easiest ways to use a chatbot to speed up processes like these is to use conversation context.

5 The hybrid model is a combination of two models.

Businesses adore AI-chatbots’ complexity, but they don’t necessarily have the talent or big amounts of data to support them. As a result, they choose the hybrid model. The hybrid paradigm combines the simplicity of rules-based chatbots with the complexity of AI-bots to provide the best of both worlds.

6 automated voice assistants

Businesses are now beginning to adopt voice-based chatbots or voice bots to make conversational interfaces even more colloquial. Why have voice bots become so popular in recent years, with virtual assistants like Apple’s Siri and Amazon’s Alexa? Because of the benefits they provide. Speaking rather than typing is far more convenient for a customer. A voice-activated chatbot provides customers with frictionless interactions.

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