Types Of Chatbots: Custom Vs Smart Vs Intelligent

  • Maxine Hunt
  • July 11, 2020
  • Comments Off on Types Of Chatbots: Custom Vs Smart Vs Intelligent
  • General

we already published a lot of articles about the chatbots on our blog. But the essentials are still missing. So the customers often request a kind of general information about the chatbots: how are they different, is there any classification, the main features of each type, what types suits for the specific business.


Today we will cover all uncovered aspects related to the chatbot classification. We hope that after reading that article, there will be nothing complicated for you. Even if any information seems familiar to you, we strongly recommend reading this article till the end. It will help you to structurize your knowledge and expand the vision on the topic in general.

Please note, there won’t be any of “scientific” definitions or terms: only the facts and informal style. We hope that it helps you to understand the topic well.


Under “chatbot”, we usually mean the computer application, that can conduct the conversation with the real human. Yeah, simple enough and there no need for complicated definition. In fact, chatbot is the kind of software, that emulates human behavior during the conversation.

According to Wikipedia, some people also call chatbots the talk bots, chatterbots, Bots, IM bots, interactive agents, or conversational agents, and that is true. There are many slang names of that software applications, but basically, they mean the same thing.

Usually, three core features are included in every chatbot:

  1. Input Data Recognition – chatbot analyzes the input text and audio and translates the data into the understandable for the machine format.
  2. Data Analysis – every conversational agent has the algorithm that processes the data in search of instructions.
  3. Decision Making – after the input data is analyzed, chatterbot should respond to the user. In fact, there is a piece of logic, that decided what to do and how to react to the input data and what to do after the response.

Chatbots help us to achieve various business goals. The most known misconception about chatbots is the thought that applications may only conversate with users to improve engagement.

Yeah, if the chatbot is used only for conversation – to entertain the users, so it is probably the most useless chatbot implementation ever. Every application should solve the business goal and improve business.

But the cruelest fact is chatbots are usually the part of the complex subsystems. They are the frontline that collects data from the user if the most interactive and user-friendly way.

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To start with, we should say, that all regular chatbots are strictly limited and have tiny skillset (in comparison to the custom chatbots). Regular chatbots use strict logic to search commands in the input text, so this makes them pretty useless in the daily use.

The regular chatbots are a kind of abstraction for the front end that collects the data from the user in the way different from the regular contact form. Let’s look at how they do it.

Imagine we have a pizzeria with the e-store. So the customers can order the pizza thru the website just pushing the desired dishes to the cart. The business owner wants to make it real to order pizza thru the chatbot.

Usually, when the customer orders pizza, he asks something like: “I want to order Pizza Margarita 21 inches to the Downing Street 1291”.

So, the sentence contains several order characteristics:

– Pizza Type: Margarita

– Size: 21 inches

– Delivery Address: Downing Street 1291

That order characteristics are straightforward to understand if you are the human, but if you are the machine, the process is slightly more complicated.

The simplest way to analyze this sentence is to split it into the list of words. In this list, it is easy to find “keyphrases” that characterize the order like “Margarita”, “21 inches”, “Downing Street”.

All the chatbot’s logic needs to do is to map those keywords to the existing menu and form the order. If there no match – return the error and connect the live person to the chat session.

But what we do, if there is an error in the input data? User mistyped “Margaritta” instead of “Margarita”, and the regular chatbot will return the error and connect the real person, distracting it from work.

So if you are developing the usual chatbot (not the smart of the intelligent one) and rely on the successful business optimization thru the automatization, you are probably mistaken – it can bring even more chaos.

The smart and intelligent chatbots are entirely different, and we describe below how exactly.


Now its time to talk about the smart chatbots also knows as smartbots. Unfortunately, there is no simple and clear definition for the smart chatbot. The smart chatbot is a kind of the collective name: we call “smart” all conversational agents, that can accurately process the input user data, even if there is the mistake or data is distorted.

The algorithms that chatbot uses for the speed processing and analysis are more sophisticated in comparison to the regular chatbot.

Let’s return to the pizza shop. When we develop smart chatbot, it can easily find mistakes in the data provided by the user. Also, it can detect errors and ask the user for a retype if necessary.

That means that the chatbot will catch the majority of mistakes and won’t distract the personnel from work every time.

From the business point of view, smart chatbots are probably the optimal cost/benefits ratio, what makes them probably the best choice for the small businesses that do not require additional and custom functionality.

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There is the single difference in intelligent chatbots and the smart chatbots: intelligent conversation agents are powered by machine learning and artificial intelligence. That makes the data processing and analysis even more complicated to understand for the person who is not graduated in Computer Science.

As was already said, as intelligent chatbots use machine learning under the hood, it most likely uses natural language processing (NLP) for the text analysis. To tell the long story short, NLP is the group of sophisticated computer techniques, that can successfully extract the data from the human speech.

Even more, artificial neural networks, that power intelligent chatbot can adapt to the human behavior. It is easier to understand if we look how intelligent chatbot development takes place for mentioned above pizza shop.

As we know, the first step of every machine learning project is data collection, cleaning, and analysis to complete the learning phase successfully. So where we can collect the sample data in the pizzeria? We can record the inbound calls and the way the operator processes them. After that, we digitize that data and with the help of natural language processing translate that data into the plain text. All we need to do is to teach the neural network according to that data.

After we have done that, we can theoretically get the neural network, that can emulate the operator behavior: how it takes and processes the order, what questions he asks during the call, and what additional goods it proposes.

In fact, the more data we use for neural network learning – the more accurate result and intelligent network we achieve. It means that the more chatbot works, the more brilliant it becomes.

The process is simplified enough, but we hope you caught the point. Intelligent chatbots are the inheritors of the regular chatbots, the result of conversational agents evolution.

Who needs intelligent chatbots? Intelligent chatbots are perfectly suitable for every business that relies on process automation. Yeah, the process of development and integration is not seamless and cheap, but the results are impressive and almost everytime worth investments.


Now it is time to talk about custom chatbots. Custom chatbots are the applications developed by the engineers on a custom platform to solve the concrete and complicated business goal.

But let’s take a step back and briefly discuss the platforms, where you can develop chatbot application on your own. It is not a secret that there are a lot of different platforms on the Internet, where you can develop a chatbot for your business. Usually, platforms have the pretty user interface where you can configure your conversation agent drag and dropping visual blocks.

Different platforms offer similar functionality, and it is a quite competitive market with its leaders. Each platform provides conversation activities on different communication platforms like the website, Facebook, Twitter, WhatsUp, Weibo, and others. The key phrase – conversation activities.

If we develop platform-based conversation agent for the pizza shop with the help of an expensive and comprehensive chatbot platform, it can recognize the order like a smart bot and forward it to the human.

Your cooks will see what people ordered thru the website, and that’s all. But catering is not only about the cooking, but it is also about resource management. Even if your cooks know, what order to do, they will need to fill your ERP system by hand. And it usually takes a lot of time.

Custom chatbots are the applications build with clear code, and it means that you can’t access the code thru the visual editor, you will need a software engineer for that. But anyway huge companies prefer custom chatbots because it is possible to execute the custom code during the conversation. Also, all intelligent chatbots are written in the pure code, and it means that they are custom chatbots.

It means that the custom chatbot for the pizzeria can not only show the order to the cooks but also automatically fill the ERP, store the order history and gain insights, and at the next visit recommend the pizzas user will like.

Another great example is the chatbot integration into the mobile application. Not to develop the separate application to interact with the chatbot, but the integration into the existing app. What can be better than to boost your existing e-commerce or human resources app with an intelligent conversational agent?