How to Develop a Chatbot in 2022 : Steps for own development

Tech stack for Chatbot development in 2022

Let’s say your day starts with one or two conversations with your clients. But during the day, there are more and more of them. You can be frustrated that even though you try, you can’t handle them all.  But what if you could have your own chatbot? It’s an intelligent solution to  answering clients’ questions or carrying out simple actions in the chat interface. It would get things easier, right?

But how to create a chatbot to succeed? What types of bots are there? What tech stack to use? Well, you can rest easy because I am going to answer all these questions and much more in this post.

See also: What is Chatbot? Chatbots tutorial for beginners

Benefits of Chatbot Development for Businesses

Why should businesses implement AI powered chatbots? There are a couple of reasons that stem from the core benefits for any service company.

• Cost-Efficiency. The AI chatbots can perform multiple actions like giving access to the software or client password reset. These intelligent solutions can work instead of 150 employees, managing about 1,6 million access queries, which will cost you less and save time.
• Clearer awareness. Consumers usually purchase products through companies’ websites or social networks but rarely talk to sales representatives, making it hard to provide a personalized experience. A chatbot integration can address this issue. So, the chatbot assistant can help you enhance your products or services by providing valuable insights of the clients’ pain points. 
• Availability. Since a chatbot is available round the clock, it allows customers to get instant answers and even streamlines the trading process. For example, Taco Bell, a US-based company producing fast food, developed TacoBot to automate the sales process and gained outstanding results.
• Customized services. Chatbots enable personalized interaction with consumers. Chatbot service provides comprehensive information about the products/services and offer support and guidance throughout the customer lifecycle.

Types of Chatbot

Typically, there are two types of chatbots: rules-based and AI-powered ones. Before proceeding to the chatbot development section, let’s consider the peculiarities of each type. It will help you understand what kind of solution your business requires.

Rule-Based Chatbots

Rules-based bots perform under ‘if/then’ logic (like bot answering FAQ). It includes a list of questions a client may ask and directions for the bot to respond. This class of chatbots can follow different scenarios and fulfill many tasks, though they are more straightforward than AI-based ones. Rule-based bots are a good solution for small organizations with particular aims.

Strong-sides of a rule-based bot

• Optimized development costs
• Advanced security
• Integration with outdated systems
• Possibility to store and transmit media files

AI-powered Chatbots

AI chatbots, also called self-learning chatbots, rely on machine learning algorithms to make conversations. Apart from perceiving customers’ intentions expressed in messages, they are also managed to scrutinize them to give better feedback. As a result, the more you teach them, the more right answers they provide.

So, if you’ve got a question on how to create an AI chatbot, you should first consider its advantages:

• Data analysis carried out by AI
• The consumers’ behavior analysis
• Multi-language communication
• Decision-making option

Now, you may ask a reasonable question: “What type of chatbots should you focus on?” Both options discussed have their own set of advantages, and it’s hard to determine the best ones. So, you need to be guided by business requirements. For example, delivering a rule-based solution makes sense if you run a small business and require just a FAQ chatbot. On the other hand, if you’re an enterprise looking for a more sophisticated solution that can make decisions itself, you should consider AI-based bot creation.

Chatbots’ Architecture and  Operating Principles

After you get acquainted with chatbot types, it’s time to figure out how they work. For example, rule-based bots contain a set of interactions based on ‘playbooks’ the software engineer set up on the backend. So, it’s common for them to operate under ‘choose options to click’ logic. For example, if the consumer buys a bag, they should pick ‘Black’ or ‘Red’ color according to a rule-based solution.

The functionality of chatbots AI-trained is based on Machine learning and AI that analyze a vast amount of data. As a result, such chatbots generate a response due to their received data. However, AI bots require a training period, so their creation is a resource- and time-consuming. Further, you’ll know how to build AI-powered bots for your client’s satisfaction by selecting the appropriate technologies and frameworks.

Despite the solution complexity, the chatbots have identical architecture. However, such software solutions become more complicated after incorporating additional elements for achieving more natural communication. Therefore, I have prepared the picture to assist you in navigating the murky waters of chatbots’ architecture.

Chatbot Integration with External Systems

It’s highly important to provide smooth data exchange to solve enterprise’ issuer correctly. However, data transfer is time-consuming and error-prone if done by hand. This is where automated integration technology comes into play. Chatbot integration with the external software allows you to accelerate bot task accomplishment, boost service quality, save funds and time, and more.

But what is the external software your bot can be integrated with? Here are the most popular (but isn’t limited to them) chatbots-systems integration:

• API
• CRM
• CMS
• Google services

Let’s take a closer look at each of them.

The integration methods are diversified, so programmers apply Application programming interface (API) to adjust to a particular messenger or app settings. During this process, specialists deal with two main design models: REST and SOAP. Despite the architecture differentiation, both techniques employ the HTTP protocol. API can also serve as a mediator between a chatbot and a server submitting the last one all the data from the consumer.

CRM and CSM systems are effective tools for interactions with your clients. So it’s critical to integrate your newly built chatbots with them. It will allow you to improve the cooperation process with customers, store their personal data, and process this information effortlessly.

If you integrate your chatbot assistant with Google services (let’s say, with Google Sheets), you can enter the required data in Google Sheets doc, and the bot will employ it as an answer for a future question. So for example, you can create a phone number reminder. This way, you put  your fellows’ names and phone numbers in Google Sheets, and the bot will display the entered info on your gadget’s screen.

There are many regards to making your own chatbot integrated with external software. You should only scrutinize the functionalities you need the most and select a system for incorporation.

Chatbot Development Stages

Here is a step-by-step approach on how to develop your own technical assistant.

1. Consider customers’ expectations and pain points
2. Determine a platform to integrate with chatbots
3. Find and engage skillful developers
4. Select the tech stack to be utilized
5. Test and launch

Now, let’s detail every mentioned stage of building a chatbot.  

1. Consider Your Customers’ Expectations and Pain Points

The process of creating a chatbot is not as careless as it seems for the first time. The core goal of chatbot development is to deliver a better experience. So, first and foremost, you need to start with a survey to reach that goal. Perform market analysis, define your buyer persona, and set up business goals following your clients’ needs. This way, you can identify customers’ expectations and figure out how to make a bot app in a more effective way.

Knowing customers’ pain points will allow you to generate a list of the required functionality. For example, your customers need to be notified of delivery time if you run a logistics business. Hence, you need to integrate a calendar into your bot solution. But bear in mind that the chatbot’s design should be intuitive and user-friendly despite any modifications.

2. Determine a Platform to Integrate With Chatbot

The powerful side of chatbots is that they enable integration with various communication applications. But in this case, you should have a deep understanding of your target audience to define what app suits them best.

For example, you would like to create your bot for an application or corporate website. It’s also worth mentioning that you can create a chatbot in messaging apps like Telegram, Skype, or Facebook Messenger.

3. Hire and Involve Skillful Programmers

Finally, cooperation with a reliable vendor is vital if you need a custom AI solution with plenty of cool features. The market offers a lot of template solutions. However, they may not cover your unique business needs due to opportunity limitations, so working with living persons is better to get an end-quality chatbot.

When selecting a tech partner, look for the best quality-price ratio and pay attention to the vendor’s experience. You can employ an in-house team, cooperate with freelance programmers, or turn to experienced outsourcing companies.

Freelancers. Cooperation with independent contractors is suitable for carrying out small activities and upgrades. The problem is freelancers cannot be responsible for a full-cycle chatbot development service and may leave a project unexpectedly — without saying a word.

Assembling an in-house team. This approach will be perfect if you want to be fully involved in talkbot creation and have strong management and leading skills. The main benefit of this option is a team being available round the clock and a smooth communication process. However, this alternative goes along with additional expenses (e.g., office rent, software, hardware, taxes, etc.) and isn’t seized for companies with a small budget.

Working with an outsourcing vendor implies that you outsource your product creation fully or partially to another company. You can choose any software development companies from popular outsourcing regions that fit your resources and requirements. Outsourced bot development has many advantages, such as affordable costs for IT services, a great pool of talented specialists, and a flexible cooperation model. 

4. Select the Technology Stack to be Utilized

If you ask yourself something like, “how do I build a user-friendly chatbot and turn it into profitable assets?” you should be aware of basic talkbot development frameworks and tools. The question is how to choose the proper tech stack with so many options available. The frameworks will allow you to make a complex bot solution that will meet users’ expectations and help you stay productive and successful. But if you pick this variant, you’ll get a chatbot with limited features. 

I will tell more about creating a chatbot app describing technologies more precisely in the section below. Keep reading it.

5. Test and Launch

You should conduct thorough testing of the newly built functionality to receive a bug-free and easy-to-use application. During this stage, you should also ensure whether a chatbot app follows users’ expectations and requirements. And even since your product is ready to use, you need to polish it, constantly tracking and modifying the conversations. Bear in mind that professional companies provide their clients with a full range of Quality Assurance so you can present your tech assistant to the market without bugs.

Technology Stack for Building a Sure-Fire Chatbot

Now, let’s talk about the technology infrastructure you should consider to create a bot.

Chatbot development refers to low code no code app development, but they can also be made using chatbot constructors and frameworks that I’ve described below

Chatbot Maker Solutions

To develop a talkbot aligning with your business’ requirements, you can apply a chatbot maker solution. They’ll assist you in building a bot with an aim to business success, an educational or a healthcare one. But keep in mind that such solutions are limited in terms of functionality, which means your bot will be pretty straightforward. Therefore, I have prepared a list of famous bot constructors to consider while making your talkbot solution.

ChatBot. This builder enables bots creation aimed at messaging apps, Facebook pages, and websites. So, how to make a chatbot using it? There are a lot of different templates designed for recruitment, booking, or sales assistants. During communication, you can also draw up dynamic answers with buttons and pictures. Moreover, you can test your upcoming bot before launching.

Motion.ai. HubSpot, a leading marketing and sales software company delivered Motion.ai to make rock-solid chatbots. This service enables you to create and launch bots to the website or apps (e.g., Slack, Facebook). You can monthly develop two well-trained chatbots with 1000 messages capacity.

QnA Maker. If you’re looking for a constructor to build a FAQs bot, Microsoft QnA Maker is an excellent (and quick) option. All you need is to share the FAQ pages you need to make a bot with a user-friendly interface. Besides, the developed assistant will be self-learning supporting about 40 languages.

Botsify. This bot constructor with omnichannel maintenance enables the development of chatbots employed for websites, Slack, Facebook messages and pages, etc. In addition, you can also design bot assistants for customer support automation with such features,  integration through ML, Smart AI, and so on. The service offers a two-week trial period; on the expiry of this period, you need to select a subscription plan.

Talkbot Development Frameworks

If there is a need for a chatbot to address complex solutions, bots constructors are not a good option to consider. Instead, focus on creating a personalized chatbot assistant that will allow you to cover your unique business needs. You can employ a wide range of frameworks during the development workflow. However, this solution requires a particular skill set to integrate the following frameworks.

IBM Watson. IBM Watson allows you to build a bot with multi language support. It gained immense popularity due to its architecture enabling custom AI chatbots building with a multilingual function. This tool supports different platforms and provides a monthly trial period. Its fundamental activity is to get questions generated with natural language’s help and bring replies to them.

BotKit. BotKit is created to build chatbots for companies. This framework contains a wide range of useful libraries and plugins that deliver outstanding functionality, such as metrics or statistics, so the question of how to develop a bot using BotKit won’t be tricky for you. Moreover, the tool allows users to work with scripted dialogs and maintains actions comprising branching logic, questions, and other dynamic behavior.

Pandorabots. This framework enables chatbot creation through animations. Such bot assistants can be created utilizing the open standard of the AIML (Artificial Intelligence Markup Language). For instance, the Superfish chatbot was made using the Pandorabots framework. This bot performing the role of English tutor was a perfect solution for some Chinese areas that lack English-speaking people.

Wit.AI. Wit.AI makes it possible to bring bot solutions to life with the help of machine learning for various message platforms. This NLP framework can be coupled with Ruby, Node.js, and Python. Using this tool, you can design, test, and implement multilingual interactions for free without any other restrictions. So, the question of how to develop my own chatbot assistant wouldn’t be stressful for you.

Remember: it’s not sufficient to use constructors to create an AI-powered chatbot. After the development process is completed, you need to teach your bot how to form phrases correctly, write requests like a human, and understand the pronunciation.

You should train the bot to comprehend how to split things into essential ones and unnecessary noises. In order to do that, the chatbot utilizes language and acoustic models that enable self-learning and experience accumulation. The language model helps the bot assistant comprehend the speech correctly and sequentially. The acoustic module transforms the words pronounced into digital information that will correspond to particular phrases. 

Then, the talkbot should comprehend the sense of the speech perceived. How does this intellectual process go? First, it matches the phrase with previously employed learning templates and finds the most appropriate answer. After that, it compares the received data with a specific information type (such as e-commerce, travel, hospitality, and so on). Finally, your talkbot needs to be taught to comprehend the phrase submitted in context and prepare a correct reply.

As a result, you can build your AI-based bot regarding different stages from development to chabot teaching and support.

See also: How does Chatbot boost your business?

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ABOUT AUTHOR

Vitaly Kuprenko is a writer for Cleveroad. It’s a web and mobile app development company with headquarters in Ukraine. He enjoys writing about technology and digital marketing.