How To Develop a Chatbot
Chatbots use natural language recognition capabilities to discern the intent of what a user is saying, in order to respond to inquiries and requests. The problem is, most chatbots try to mimic human interactions, which can frustrate users when a misunderstanding arises.
A ‘chatbot’ as the name suggests is a machine that chats with you. The trick though is to make it as human-like as possible. From ‘American Express customer support’ to Google Pixel’s call screening software chatbots can be found in various flavours.
Chatbot platforms to build your first bot
- IBM Watson Assistant
- TARS
- Amazon Lex
- Verloop
- Chatfuel
- Azure Bot Service
- Collect.chat
How to build a chatbot and how does it actually work?
The earlier versions of chatbots used a machine learning technique called pattern matching. This was much simpler as compared to the advanced NLP techniques being used today.
What is Pattern Matching?
To understand this just imagine what you would ask a book seller for example — “What is the price of __ book?” or “Which books of __ author do you have?” Each of these italicised questions is an example of a pattern that can be matched when similar questions appear in the future.
Pattern matching requires a lot of pre generated patterns. Based on these pre-generated patterns the chatbot can easily pick the pattern which best matches the customer query and provide an answer for it.
A ‘chatbot’ as the name suggests is a machine that chats with you. The trick though is to make it as human-like as possible. From ‘American Express customer support’ to Google Pixel’s call screening software chatbots can be found in various flavours.
How does it actually work?
The earlier versions of chatbots used a machine learning technique called pattern matching. This was much simpler as compared to the advanced NLP techniques being used today.
What is Pattern Matching?
To understand this just imagine what you would ask a book seller for example — “What is the price of __ book?” or “Which books of __ author do you have?” Each of these italicised questions is an example of a pattern that can be matched when similar questions appear in the future.
Pattern matching requires a lot of pre generated patterns. Based on these pre-generated patterns the chatbot can easily pick the pattern which best matches the customer query and provide an answer for it.
Code-based frameworks for bot development
Without exactly software, code-based frameworks for bot development need a programming language, but they give developers the various tools to customize their chatbot. These frameworks supply the database tools, analytic features, and infuse AI into the bot.
Some frameworks for developing a chatbot from scratch are:
Microsoft bot framework
Wit.ai
API.ai
For non-developers, use chatbot creation software
Among the many advantages of hopping on board the chatbot train in 2019 is the actual fact that chatbot creation websites are everywhere. What’s more, many of these sites offer low- or no-code options for users, specifically for folks with no coding background whatsoever.
Conversely, some chatbot creation sites allow users at hand off the responsibility of actually creating the bot to someone on the staff.
For example, Instabot gives users the option to obtain a free, custom-built bot created by one with their developers. On their site, their on-page chatbot prompts the website visitor with buttons with sample queries from which the user can choose. Options like Start TRIAL OFFER and Custom Bot Built free of charge guide interested parties to some extended questions that help direct them to the correct “chatbot architect” (AKA the developer) who’ll be creating your chatbot for you. Their site bot will ask for more information, such as contact details, the net address for the website you want your bot to be linked to, and what tasks you want your chatbot to have. These queries ensure that the correct chatbot architect is tasked with creating your site’s bot.
As seen above, the Instabot chatbot can understand the info I type to it; however, it is clear that the chatbot contains a combo of canned responses and natural language processing (NLP) capabilities.
Which means that the bot is programmed to identify FAQs and key phrases/responses, as well as identify the the different parts of a contact address. Instabot understands that an effective email should contain words before and following the @ sign, and also a .com/.net/.org ending to indicate that it’s indeed a viable email.
Creating a chatbot through Facebook Messenger
Possibly the most typical method, Facebook chatbots seem to be to be the tool of preference for most companies, big and small. Why is this program ideal will be the multiple tools that Facebook provides to users. There’s a whole page dedicated to developers; however, non-developers considering creating a chatbot can make use of it as well (thanks to the user-friendly site directions).
Creating your chatbot through Facebook and hosting it via Messenger is suitable for many because Facebook provides tools and guided directions about how to really build your bot. Users who go this route will wrap up learning some components of coding along the way, but it’s low-code so that even beginners can create a bot independently. Plus, many people worldwide use Facebook, which means that your chatbot will be obvious to millions.
Another facet of chatbots hosted on Facebook is how they could be built-into an external site (i.e. your home website can have the chatbot’s code embedded into it!). Now, you have the choice for users to access your chatbot on Facebook directly or from your homepage, providing them with an option as well as simple accessibility.
