While some of current technological inventions are just a luxury, we cannot deny that a lot of them have become a necessity in today’s world. Still, we are not satisfied with ourselves and the innovations that we have already made. We keep pushing the limits to make our lives simpler by coming up with new ideas every day. One such innovation is the chatbot.
Do you want to drive traffic and engage more customers on your brand? Do you wish to increase revenue and reduce customer service cost? Chatbots can help you get there.
Chatbot is an artificial intelligence program that can simulate human conversation through voice commands or text chats or both. Nowadays, there are many chatbots available in different messaging applications like Facebook messenger, Slack, Telegram etc. Many businesses like eBay and Uber have come up with their own bots to help customers with their queries and bookings.
These chatbots work on the machine learning algorithm and have access to a huge data set of information from which they can answer user’s queries accurately and quickly. As these machines learn from the information provided by humans, they become more intelligent day by day and will be able to answer even more complex questions over time.
With the help of this technology, humans can get answers for all their queries without much effort at any time of the day without having to wait for anyone else to reply back to them. You must be knowing about some of the popular Chatbots like Apple Siri, Google Assistant, Amazon Alexa. They help us in completing our daily tasks like setting alarms, getting directions, booking tickets etc. These tasks were previously done by humans and were time-consuming as well but now we can get them done in a matter of few seconds.
The market is all set to go big on chatbots soon. According to the recent research conducted by Grand View Research, Inc, the global chatbot market size is projected to reach 1.25 billion USD by 2025 registering a CAGR of 24.3% during the forecast period. The adoption of AI technologies in the retail sector is expected to accelerate the market growth for chatbots over the next few years.
Chatbots have penetrated various industries like eCommerce, banking, healthcare, and many more.
What is a Chatbot?
When you think of robots, you might think of a machine that looks like a human. Chatbots are nothing like that. A chatbot is basically a piece of software that you can add to your website, app or messaging service that will automatically respond to questions and triggers you set up in a conversation, as though it were having a text conversation with someone.
Choosing the Right Technology Stack for Your Chatbot
You’re probably familiar with the term “tech stack” — but what is a tech stack, and how can you use it to build your own product?
It’s a simple idea that’s become crucial in modern web development. A tech stack refers to the combination of technology products or services used to create or run a website or application. It usually refers to the specific languages, frameworks, databases and tools used by developers to build an app.
When developers talk about their “tech stack,” they’re referring to the specific tools they’re using at that moment. But it can also refer to a larger set of tools that are used together regularly for a particular purpose — for example, a specific database might be part of several different tech stacks for web applications.
A good tech stack can help you get your product out the door faster, because it comes with well-tested components chosen for their reliability and effectiveness. However, there’s no “best” tech stack for every business or every project: Your choice will depend on your goals, your budget, and which technology products you have access to.
Chatbots are useful for a range of industries, but for most businesses, the main use case is sales and marketing. This means most chatbot projects will be best served by the tech stack below:
A chat platform such as Messenger or Slack
- A connector between your chatbot and the chosen platform
- An NLP framework that can understand user intent
- A backend application that contains your business logic (in other words, this is where your chatbot lives)
- An analytics tool to track performance
You can build your Chatbot using a combination of the tech stack mentioned below:
- API calls and HTTPS connections are handled by the server
- Cloud Service provides chat storage for a better understanding of the intent, appropriate response and scalability
- Machine Learning Algorithms and Natural Language Processing techniques are used by NLP framework intelligent chatbots to gain better knowledge of the syntax and semantics of sentences.
Five Tips to Carefully Select the Right Tech Stack for Your Chatbot
- Define the project scope: It is important to study the details of the project and identify its feasibility, scalability, and technical complexity. This will allow you to set KPIs for your chatbot and identify what technologies you need to achieve the results you want.
- Map out a conversation workflow: If you’re building a bot, you can use RealtimeBoard and BotMock to design conversation flow. If your goal is a voice assistant or voice-activated product, consider using tools like Dialog Flow or SnatchBot.
- Development: Combining different features, functionality, frameworks, and tools into a complete software program that meets your requirements
- Scalability: Let analytics be your guide by keeping an eye on the KPI’s you have set and how they compare with your goals.
Factors to Consider When Designing Chatbot Tech Stacks
When building a chatbot, you will want to keep the following factors in mind:
1. Message Interface
Message Interface is a Chatbot’s interface to the users, where the users can type their queries and get responses. In case you are designing a conversational chatbot, it becomes mandatory to leave enough space for users to type their messages. It is not only about typing; it is also about speech recognition and voice commands. The interface must be designed in such a way that there should be frictionless communication. If you fail to do so, then there will be many chances of the user churning out of your chat flow.
To effectively design a chatbot, you must choose the channel through which the people will interact with your chatbot. These channels are called interfaces. For example, WeChat is the primary platform if your focus is on Asian users. If you work with startups and developers, Slack is a great tool. Skype and Microsoft Teams are better suited for business use, where you can create a chatbot for employees of a large corporation with significant data protection concerns.
What particularly makes sense to you?
Once you decide on the interface, it makes it easy to start building on it. These platforms have their own SDKs (Software Development Kits) or APIs (Application Programming Interface) which can be used to build on top of an existing platform.
Your interface choice also depends upon where your target audience uses these channels more often. For example, if your target audience is millennials, then Facebook Messenger may be the best choice for you as a platform since millennials use Facebook Messenger for almost all of their daily communication needs. It would make sense to design a chatbot for them in the same place where they are already present rather than asking them to go somewhere else to talk to your chatbot.
2. Building Bot Flow Graphs
There are many ways to build a bot. While some bot builders offer low-code platforms that enable anyone to build a bot, other solutions require more technical expertise and coding knowledge. You can even create a bot in your existing application using an API. The type of technology you choose is based on the goals and needs of your business.
Before getting into building a chatbot, you first need to choose the right platform to ensure that you have all the tools and support you need to build and implement your business solution.
The following are some of the things to keep in mind when choosing the right platform for your business:
- How much control do you want over your bot? Are you able to customize it?
- What is the use of coding? Do you want a low-code or no code solution?
- Does the platform offer additional tools such as analytics, A/B testing, audience segmentation, and natural language processing (NLP)?
- How much help does the platform offer for deployment? Is there support for multiple messaging channels?
The chatbot platforms can be divided into two categories: code-free or code based solutions. And each one has its own set of advantages and disadvantages.
3. Conversation Type
This is perhaps the most important decision you’ll make when creating a chatbot. The goal of any bot is to simulate a conversation with a human being. The exact nature of this conversation will determine the technology that works best for your needs.
Here are two types of bots:
- Question-answer based bots
- Full-fledged conversational AI
The first one is pretty self-explanatory: the bot can answer simple questions, provide information, and that’s it. In other words, it is usually used as a FAQ tool that helps you reduce support costs by answering user questions before they even ask them. Since this type of chatbot doesn’t require much development effort, there are plenty of tools ready to help you achieve this goal, such as QnAMaker by Microsoft or Operator by Intercom.
The second type is more complex and requires huge efforts to build and maintain, especially if you need to create it absolutely from scratch (instead of using an existing framework). This type of chatbot can solve complex problems, understand human speech in context, and provide personalized recommendations based on this understanding.
The most important part of chatbot development is to understand the objective of the bot. A conversation type is a way to classify applications into different categories based on their objectives and functions.
There are three types of conversations that help us understand the objective of the bot :
Keyword-based bots: These bots recognize keywords and then provide a set response. These bots work best for simple applications that require limited functionality like providing a product catalog or providing basic information about your business.
NLP-based bots: These bots are able to understand complex user responses. They can process natural language and use NLP techniques to understand what the user is saying and provide an appropriate response. These bots are suitable for more sophisticated applications like booking a table at a restaurant or ordering from a menu, with some assistance from human agents if required.
Hybrid bots: These bots have the characteristics of both keyword-based and NLP-based bots. These bots may start as simple keyword-based responses and go on to become NLP-based ones with more data gathered over time.
5. Supervised Learning
Think of supervised learning as the training process. The more a chatbot is trained, the better it will be proficient in responding to various user queries. A chatbot can’t function without human intervention, especially when it comes to improving conversation flow, adding new intents, and expanding its knowledge base. The process of a human team supporting the chatbot is known as supervised learning or training. This procedure might be carried out during or after the chat.
There are a few ways to train your chatbot:
By adding new intents: To create great conversational experiences, you need to develop multiple intents and add them to your NLP engine so that it can understand user input better. A simple example would be to create an intent for “greeting” and include utterances like “hello”, “hi”, “howdy”, etc.
By adding examples (utterances) for each intent: You need to provide multiple examples of user conversations for each intent so that the NLP engine recognizes them correctly and responds appropriately in future conversations. Using the above example, pop up messages could include – “Hi! How is my day looking today?” and “Hey, what’s going on?”.
6. Human Intervention
Customer service is an important aspect of any company. And it is now more important than ever to be able to respond quickly and effectively in this fast paced world.The current generation of customers expects to get help anytime they need it.
The rise of chatbots has paved the way for instant customer support 24/7. But there are still some limitations to what an automated bot can do for you. Your customers will want to reach out to a human agent if those limitations start to show up.
For example, when the conversation becomes too complex or sensitive, like changing personal information, or canceling an order, you may want your customers to get in touch with a live agent instead of having a frustrating conversation with the chatbot. Sometimes, your bot may not understand what the customer is saying. Other times, some technical issues might cause problems with your bot’s response. In these cases, it is better to have a human agent ready to assist your customers.
7. Integrate API
Many bots, particularly those aimed at consumers, integrate third-party services via web services. If you have a plan to develop such a bot, it is critical to use the right tech stack that supports this functionality.Chatfuel, for example, allows you to connect to Zapier.However, most visual editors do not allow integrating external web services. The best solution to resolve this issue is to code the bot logic and use REST APIs.
The steps in the integration process are as follows:
- The chatbot receives a user request (e.g., a message)
- The chatbot sends an HTTP request to an external web service and passes user data as parameters
- The external web service analyzes parameters and returns a response to the chatbot
- The chatbot responds to the user with the received data from the web service
8. Language Support
It goes without saying that you can determine the language of your chatbot on the basis of your target audience. The majority of platforms handle English quite well, but not all of them can include other languages as well. Even when the language is supported, the performance is not always up to par.
Companies such as Facebook Messenger, Slack and Kik have their own NLP engines which are capable enough to support a couple of languages. Since all these platforms came from different backgrounds (Facebook, Skype and Slack), they had different purposes to serve in the first place, so naturally they also had different types of users speaking different languages.
9. Cost- effectiveness
When it comes to business, one of the most important things that you need to consider is cost-effectiveness. The same goes for choosing the right software solution for your business. Especially if you are just starting out and don’t have enough budget to spend. However, it is crucial to consider the price of software solutions that help you anticipate your user growth. Mostly, you will find business models such as Free, Freemium, Pay per messages/API Request, Pay perusers on the platform, and Subscription.
The ideal way to find out which business model best suits your company is by looking at your budget and comparing it with the prices of different pricing models available in the market. For instance, a Subscription Model would be cheaper than a Pay Per User plan if you have a large number of users. Similarly, you can also opt for Freemium or Free services if you have a small user base.
If you are a business owner, you can use chatbots to promote your product or service. It will help you to provide better customer service and engage more with your clients.
Creating a chatbot is not an easy job. You need to make many decisions before creating it, such as the technology stack that you will use in the development process. When making these decisions, consider the type of chatbot that you want to create, whether it would be a text-based chatbot or voice-based one.
The main idea is to make it feel as natural as possible. Maintaining the right tone of conversation is a crucial way to achieve this goal. The tone of voice should be in line with your brand, so the audience always feels like they are talking to a person, not a robot.
We provide promising mobile app and web development services that will help you integrate a chatbot easily and effectively into your mobile or web app to serve the requirements of your clients.