<script type="application/ld+json">
 "@context": "https://schema.org",
 "@type": "BlogPosting",
 "mainEntityOfPage": {
   "@type": "WebPage",
   "@id": "https://www.engati.com/blog/wikipedia-does-not-tell-you-about-making-chatbots"
 "headline": "Wikipedia does not tell you everything about making intelligent chatbots",
 "image": "https://global-uploads.webflow.com/5ef788f07804fb7d78a4127a/608ff7387b87521d75a07a8a_What%20Wikipedia%20can%E2%80%99t%20tell%20you-p-1600.jpeg",  

"articleSection" : "How have chatbots transformed user experience?",  

"articleBody" : "Chatbots have changed the way companies reach out to their target market. With <A href=\"https://www.engati.com/blog/chatbot-trends-machine-learning-artificial-intelligence\" target=\"_blank\">Natural Language Processing</A> (NLP) entering the mainstream, chatbots which are empowered by the NLP are slowly changing the way we seek information.",
 "author": {
   "@type": "Organization",
   "name": "Engati Team"
 "publisher": {
   "@type": "Organization",
   "name": "Engati",
   "logo": {
     "@type": "ImageObject",
     "url": "https://global-uploads.webflow.com/5ef788f07804fb9e0aa41273/60950e66372af76cf098f036_engati%20logo_color.svg"
 "datePublished": "2020-11-17",

"dateModified": "2021-05-31"

Drive to Reimagine

Wikipedia does not tell you everything about making intelligent chatbots

Engati Team
Nov 17
5-6 mins

Table of contents

Key takeawaysCollaboration platforms are essential to the new way of workingEmployees prefer engati over emailEmployees play a growing part in software purchasing decisionsThe future of work is collaborativeMethodology

Most of us have used chatbots at least once in our lives. When I first heard of chatbots, embarrassed of living under a rock, not knowing what exactly this technology is (though I’d use it daily), I quickly turned to my intellect savior, “The Wikipedia”.

So as I read through the page, I could hardly get a hold of all the technical implications of these alien bots. Honestly, I lost my way somewhere in between the lines and started thinking about doughnuts. That’s when I opened my food delivery app and began to look through the menus, when suddenly a suggestion popped out of nowhere, customized to my preferences. I was impressed!

After I finally ordered doughnuts from my favorite food chain, it suddenly happened that I had to cancel the order. What do I do? Where do I go? Who do I contact? Do I have to wait for 20 minutes on the phone to just get to the right person to solve my issue?

Amid my panic attack, my friend suggested using their chatbot, which would assist my problem and provide a solution instantly. Voila! God bless technology! So this is where my research about chatbots starts (Thanks to doughnuts).

Therefore, this time all curious and impressed, I turned to Wikipedia once again to learn more about chatbot building. But I found out that Wikipedia could not possibly cover the topic in depth! Hence, in this blog, we’re going to discuss “What Wikipedia Can’t Tell You About Making Chatbots”. But first, let’s start off with the basics.

What are chatbots all about?

A chatbot is a computer program that conducts conversations with human beings and executes automated tasks. Though chatbots have been there since the late '60s, they’ve achieved full potential recently. Earlier, “bots” had been in the industry for quite a while, taking up repetitive tasks and automating them, in turn speeding up the business process and helping the organization run effectively. Then came the “chatbots,” which imitated human conversations by taking hints and ‘cue’ words and helped develop the customer care services. But today, chatbots have evolved and reached such a great platform that they’re taking over all sectors of industries.

How have chatbots transformed user experience?

Also known as “digital transformation,” chatbots have played a major role in transforming the user experience in general. Imagine you want to cancel an order on a food app; what are you going to do? You automatically think of chatbots. Customers look for efficiency, ease, and authenticity while conversing with a bot. Chatbots have changed the way companies reach out to their target market. With Natural Language Processing (NLP) entering the mainstream, chatbots which are empowered by the NLP are slowly changing the way we seek information.

How to create a chatbot?

So now that we have brushed up on the basics let’s get to the technical aspects of how to create a chatbot! There are mainly two approaches to this, with different types of website chatbots in each.

First would be the typical Rule-based approach, which requires heavy coding, consuming time, resources, and money. There are three types of chatbots built when you use this manual approach.

The rule-based approach builds rule-based chatbots which only respond to specific commands and are basic in nature. Then comes the AI chatbots that are smarter and better, reading and responding to natural language. The third one is the hybrid chatbots which comprise both rule-based and AI formats.

While making smart chatbots, a builder has to comprise conversational dialogue training. Such dialogue training is done with the help of artificial intelligence, hence the name “AI chatbots.” The building process of AI chatbots is pretty innovatory, mainly comprising of these three protocols-

  • Data processing:Data processing is basically a multi-step natural language processing workflow to correctly recognize and infer free input text. This process requires serious engineering efforts when the input is multi-line/multi-objective.
  • Context:This helps the program to learn the interdependence between dialogues and the course of actions so that chatbots can drive the conversation in the right direction. This keeps the availability of previous chat conversations (message logs) in check, in order to build knowledge graph.
  • Chatbot training:Providing training to learn new conversations at all times to improve AI chatbot's performance with the help of unsupervised methods based on machine learning techniques.

The second approach would be opting for services which render you a substructure to build your chatbots on, without the need for coding. This proved to be a salvation for those bot-building enthusiasts without programming skills. In this process, a bot builder uses one single code that can be used by all, at all the platforms available.

To create your own chatbot in 10 minutes, visit us at Engati.

What are the design elements to use?

Design elements of a chatbot depend on the type of messaging platform you choose to install the bot at. A few top design elements that can be considered while creating a bot are -

  • Buttons:Buttons prompt actions when the user clicks on them. Interactive buttons can be added to help the user make decisions faster. It is the bot that makes the user make decisions.
  • Get started button:This is an intuitive feature that prompts the user to set the bot into action. A chatbot built for Facebook messenger cannot do without this feature.
  • Cards:This feature is used to serve into like links, text, images, and buttons as blocked containers. The blocks are visible when the user’s phone turns sideways. The user can select the card that is relevant to him.
  • Smart Reply:This feature is useful when the chatbot is context-aware and has user information. This helps a user respond fast to the chatbot’s query without the user attempting to type anything.
  • Quick Reply:A user can use this feature as a response button.
  • Persistent Menu:A user can use this feature to steer his way to another portion of the bot that is not readily available.

How can you improve your chatbots further and user experience?

Now that you’ve got the gist of how to build chatbots, let’s discuss about a few implications that can further improve your chatbots to deliver the best user experience.

  • Know your potential user and understand your target audience.
  • Read the user sentiment and make your chatbot emotionally rich.
  • Welcome the user.
  • Guide the user.
  • Reduce user struggle.
  • Listen to the user’s voice.
  • Understand the intent of the user.
  • Infuse intelligence quotient into bots to reply to complex queries. You can use NLP to do this.
  • Use NLP AI.

Hope this article helped you with what you were looking for. To read more about our chatbot ecosystem, check us out!

Happy botting!


Engati Team

At the forefront for digital customer experience, Engati helps you reimagine the customer journey through engagement-first solutions, spanning automation and live chat.

Andy is the Co-Founder and CIO of SwissCognitive - The Global AI Hub. He’s also the President of the Swiss IT Leadership Forum.

Andy is a digital enterprise leader and is transforming business strategies keeping the best interests of shareholders, customers, and employees in mind.

Follow him for your daily dose of AI news and thoughts on using AI to improve your business.

Catch our interview with Andy on AI in daily life

Continue Reading