In recent years, the biggest players in the technology market have been talking a lot about Artificial Intelligence and how it’s going to change our lives in the near future. Already today we find ourselves surrounded by smart devices that help us with various tasks – from telling us the weather forecast for the upcoming week or playing a song that was stuck in our head just a few seconds ago, to intelligent kitchen assistants capable of performing complex mathematical equations.
* are software applications (scripts) used to automate tasks and actions. Users can ask chatbots questions in a conversation-style interface and often receive relevant answers. There are a number of examples of this kind of software being used already: weather forecast bots, search query tools, Facebook Messenger chatbots, and many others.
What is interesting about this trend is that one does not necessarily need tons of money and programmers’ workdays in order to get their hands on some machine learning abilities. All you really need nowadays is an idea for a product, some time to spare for exploring the market of existing intelligent applications, and most importantly, a clear understanding of what you are trying to achieve.
One thing which is more or less common for all intelligent machines today is that they can communicate with human beings. However, even though this seems like an obvious ability at first glance, it is not as easy as it might seem: take Amazon’s Alexa and Google Assistant – probably many people will agree that these two virtual assistants have a lot in common but one still might find their daily interactions rather uncomfortable. The same can be said about Siri and Cortana: while both use bots under the hood, they were designed for different purposes and as such work in slightly different ways.
Why does all this matter?
Well, when it comes to chatbots. It would be a shame to build an application that does not feel natural in the way it interacts with its users. And in order to achieve this goal you need:
A solid technology stack ( Facebook Messenger Facebook Bot API and/or Telegram Bot API ); Understanding of your audience; A clear idea of what is it that you want to achieve.
Bear in mind though that these 3 aspects are not always equally important for every chatbot project: for example if your bot is supposed to help people navigate through their daily routine (eg. check the weather, track their orders) then most likely understanding will play a more significant role than technology or business goals behind the product itself.
On the other hand, if you want your bot to be perceived as an advanced AI – capable of making decisions on its own and understanding complex commands in different languages – tech stack becomes equally important since it defines how easy or hard it will be for programmers to achieve that goal. As usual, the user audience matters at all stages of the chatbot development process but when it comes to deciding whether our solution should act as a personal assistant or rather resemble the thinking machine, things get slightly more complicated.
So, how do you make sure that your product idea is good enough for turning into a real business? What are the key features of a chatbot designed for daily use by its users? And what should one keep in mind while designing an application whose purpose is to either impress or to put users into a state of flow?
Let’s find out below.
First things first – what is your endgame? Do you want to sell products (and if yes, which ones?) or do you plan on promoting your brand via chatbot application? Or maybe you are just curious about whether the idea of building something like this actually works and want to start small with some kind of testing? Whatever might be the case, bear in mind that one of the most important factors behind designing an effective chatbot is understanding its purpose. This means that even though it might sound obvious at first glance, it is better not to get carried away while trying to design something that would either imitate advanced AI without having the adequate infrastructure or act like some kind of eCommerce hub without having the adequate knowledge to achieve this goal.
Let’s start with the first one: if you are more into AI than into marketing, then chances are that you will be better off designing your chatbot application for Facebook Messenger. It is now possible for anyone to build a basic natural language processing system capable of understanding complicated commands and responding accordingly even though currently there exists no possibility of running paid campaigns or selling virtual goods via this platform.
Building an advanced chatbot will require hiring a few skilled developers not only because of the technological barrier but also due to the fact that one needs either have experience with Node.js or know a good programmer who does. Not everyone understands why they need to pay up for something which anyone can create by installing the appropriate software and clicking on a few buttons as long as their end goal is limited to either updating customers about new products or convincing them that AI knows everything.
What if you already have knowledge of what you want your chatbot to do?
It would still make sense to check out Facebook Messenger first because it provides faster development thanks to Wit.ai, allows building more complicated bots, and runs paid campaigns at a lower cost. Once again, Telegram is still worth considering because its bot API offers more opportunities for reaching the audience. Things become trickier when it comes to selecting the right platform for deploying chatbots designed to either answer queries or complete specific tasks. Even though these two use cases are both useful and according to statistics, currently dominate over everything else, they require totally different approaches which should be defined before even thinking about entering any kind of development process.
If you plan on building what can be referred to as a “knowledge base”, then chances are that you will need to design your web app using React.js or Angular.js (or other similar frameworks) followed by submitting it to the appropriate directory (for example Chatfuel ) in order to turn it into an application capable of answering users’ questions within the limits set by the chosen platform. Unless you want to invest a lot of time and money into your project, it will be advisable not to develop natural language processing or machine learning algorithms as the only possible outcome might be forcing users to either ask very specific questions or find their answers somewhere else on the Internet.
However, if you already have an app created before developing a chatbot, make sure to check out whether it is possible to add a chatbot to your project and what benefits this might provide. I would also advise you to read my article about the differences between Slack and Telegram because both of them can be used for building big and profitable projects.
Before we wrap things up, there are two more points that need to be discussed: firstly, how much time does one need in order to create a functional chatbot on Facebook Messenger or on Telegram? The answer depends mostly on the chosen development tools but chances are that it will take somewhere between 8h – 24h depending on whether you have previous experience with these or not. Secondly, what kind of costs should one expect? While some people say that all they needed was some free software, others argue that the only feasible option is to hire a professional team.