1. Home
  2. Blog

Chatbot Development From Scratch: Tips, Tricks, Pitfalls

Chatbot Development From Scratch

Developing a chatbot for your business has been a necessity for a long time. In our article, we will share our experience of how to build a chatbot from scratch, and tell you what benefits chatbot will implement to your business.

What are Chatbots and Where are They Used?

Chatbots and smart audio assistants, like ‘Alexa’, ‘Siri’, etc, have given rise to a global trend of human-machine interaction which companies can leverage to provide better services.

Bots can be used on a website, an app, in responses via e-mails, in SMS conversations, or in communication and social messaging tools such as Facebook Messenger, Telegram, WeChat, Line, Kik, Viber, or Slack.

The use of chatbots, whether in-app or on-web, provides warnings and alerts to customers and improves work capacity, particularly during non-business hours or over the weekend. They also help to stay in touch with top trends, create enhanced lead generation based on a multitude of suggestions, and provide a Personalised experience to customers. The use of bots has shown increased CTR and OR in various specialized industries including, customer service, health, blockchain, finance, aviation, and even entertainment platforms.

Why Does Your Business Need a Chatbot?

As seen on Businessinsider.com, the chatbot industry revenue is expected to rise from $2.6 billion in 2019 to $9.4 billion by 2024, with a CAGR of 29.7%. Businesses of all models and sizes are beginning to understand the importance of this technology. Thus, chatbots are upgrading all kinds of industries, from healthcare to finance, to education and e-commerce.

In fact, because of the level of challenges posed during the COVID-19 pandemic, by the last quarter of 2021, 95% of online brands are projected to use ’chatbots’ for interacting with their customers. According to data from the Webforum global agenda, WHO and CDC have now added chatbots to provide information about the pandemic to billions. So, why are many organizations jumping the bandwagon?

Chatbots are capable of providing information to the client about their conditions, managing orders, making reservations, or dealing with incidents. If you aim at better customer experience — improving the time spent on answering their questions, on solving their problems, on providing references or ideas, then you need a bot.

The beauty in having a chatbot is that it sifts through large amounts of information, providing relevant results without compromising natural language. Chatbots are more efficient than humans in routine customer servicing, mostly because they have an extensive knowledge base, search window, and speed. They are also integrated with CRMs and multiple software.

Here’s a chart from Convince and Convert, indicating more potential benefits of chatbots.

Develop chatbot from scratch

Source: Convince and Convert — 24-hour service is the highest potential benefit of a chatbot.

Bots can serve your business needs in areas such as Customer Support, Sales Channels, Information broadcasting, Financial Transactions, Questionnaire Management, etc. Before we discuss the technicalities involved in building a chatbot from scratch, let us consider some organizational steps to take to develop and integrate a chatbot properly.

Want to get an estimate of your chatbot building project? Fill out the form.

How Do Chatbots Operate?

Chatbots are digital software that is programmed to carry out online conversations with a human user through graphics, videos, text-to-speech, or simply text. Since their development, they have been evolving, especially with the ongoing advancement of Artificial Intelligence (AI) which has enabled the human voice and text to be easily converted into useful data.

This data is then programmed to interact with, question, and reply to human beings. These functions enable various applications to engage in more natural interactions. This mode of conversational user experience has totally revolutionized the way people interact with machines. Chatbots can do much more than just automating tasks: they literally ensure that every users’ experience is personalized.

We must know how to differentiate between the intelligence that makes the bot interact/ communicate and the framework on which we develop the chatbot. This is simply the technology or program that we use to develop and configure the chatbot. When building it, these two concepts are merged, but they have different algorithms.

Thus, the development platform shouldn’t be confused/ mistaken as the environment that the chatbot is going to later reside and have its conversations, like a messaging application. Although it is possible that the environment where the chatbot is to be hosted can offer a platform to develop it.

In other words, the framework of a chatbot is the development platform containing resources or tools that make it possible for developers to design, build, and sometimes host the chatbot.

Chatbot Types

AI chatbot

1. AI-Powered Chatbots

Most of these chatbots make use of what is known as Natural Language Processing. Natural Language Processing is driven by Artificial Intelligence (AI) that is built to learn, understand, and use natural languages and communication skills.

With the involvement of Machine Learning, the chatbot can learn from its experiences by automatically storing and analyzing data. During the creation process, the chatbot’s developer can also teach it how to respond and learn.

Most AI-driven chatbots allow users to control the interaction and try to ensure that the interaction is as natural as possible. AI can be used to integrate the most sophisticated and complex forms of human-machine interaction. Examples of such chatbots are Apple Inc's’ Siri, Amazons’ Alexa, Google Assistant, etc.

2. Rule-Based Chatbot

These chatbots operate according to a set flowchart or decision tree of operations. They control user interaction by promoting responses and giving specific options that users can pick as their desired response. Although they are not as flexible as AI-driven chatbots, their response is always guaranteed. They cannot function against the roles set by the developer, thus they are secure and straightforward.

Scripted bots are also capable of performing complex actions, and can be integrated with images, videos, buttons, loops, and other non-text forms of interaction. They are common in company websites and apps because of their simple structure of a flowchart or a decision tree that surely leads to one or multiple set outcomes such as product sales or customer registration, etc. Thus, they are easier to build and integrate than AI-driven chatbots.

2 Approaches to Building a Chatbot From Scratch

It’s either you’re building the chatbot with your staff or you outsource its development to already established platforms that have programmers that have already streamline the chatbots architecture to meet your requirements. Let us first discuss some steps you should take after deciding to build a chatbot with your staff (in-house approach).

Do it Yourself Procedure

  • Form a multidisciplinary team: Forming or hiring a team of diverse roles will contribute positively to the success of the initial setup phase and the maintenance phase going forward. Business and marketing teams will define the various goals for the chatbot, creative teams, and software programmers will design and develop the software experience respectively, and the software programmers will be in charge of its technical implementation and maintenance.
  • Define and set goals: Setting the chatbots’ goals is the responsibility of the company's’ business and marketing team. Some questions have to be asked to achieve this. What exactly does the company want to accomplish with the chatbot? What are the company’s present solutions/ services? What are the most used and least used services? What are the company's’ solutions to virtual human interaction? What are these interaction solutions missing? And What exactly would the chatbot do better than the existing user interaction solutions? Depending on the company's’ model, preferences, and team, the outlined questions may vary. It is necessary to define more KPI for each stage of chatbot development tied to the company’s business goals. It will serve as an indicator of the correct movement and the right decision to implement the bot.
  • Know the Chatbot’s users: By evaluating, defining, and understanding those who will make use of the chatbot, the company will be able to identify the type of devices being used. They can decide on the kind of personality to create and understand how to build a conversational solution. When ascertaining the various clients, the company has to consider multiple demographics, such as age, gender, geography, and language. Even customers’ preferences have to be taken into account. This step is vital because the success rate of a chatbot is hugely dependent on how well the company knows the customers and their various needs. The success rate doesn’t depend on how sophisticated and expensive the chatbot is.
  • Define the different devices, platforms, and channels: It is essential to establish whether the bot will use voice + text or only text. If the company decides to use both voice and text, the development team may be tempted to convert text to speech simply. This may be a mistake, as many variables come into play during simple text to speech conversations. That is why Artificial Intelligence is key to ensuring a successful bot construction. Advances in language processing via AI have given rise to proper text to speech algorithms, which ensure that the chatbot maintains some level of natural interplay.
Machine learning chatbot
  • Give a human personality to the chatbot: Just like ’Eliza’, ’Siri’, ’Alexa’ etc., chatbots and virtual assistants typically have their names. According to psychologists, when users interact with chatbots, their brains tend to believe that they are having a conversation with another human being. Since this is so, why not give the bot a personality to make it appear human and authentic? At first glance, most users mistake a chatbot for a live customer service representative, and this makes the user address their needs or issues adequately and precisely as they would to a human being.
  • Defining the functionalities: Defining and integrating the functions of the human-machine conversation/ communication is probably an essential part of the development process. It involves specifying the user cases, objectives, the creation of relevant conversation flows, and the connection to the APIs (Application Programming Interface). Almost any chatbot development begins with defining the bot transitions and the edge states description, and all the options for using the bot by the user. Here, all the teams will have to intervene, from marketing to software design and development. What questions will the chatbot ask? What are the possible answers users will have to choose? What are users frequently asked questions? Every conceivable human and machine response has to be taken.
  • Development and testing: After all the research and analysis has been completed, and data has been documented, the software design and development team will start designing and programming the conversational application. When creating solutions from scratch, the design and development team will be responsible for using Artificial Intelligence in translating conversations into code and integrating business logic across all the company's’ virtual platforms and operating devices.ces. Another crucial step in the development stage is the configuration of user-bot statistics. The statistics are used to compare the bot’s performance side-by-side with the expected outcomes and determine whether the bot is working at its highest conversation completion rate. Using such statistics, one can also see a breakdown of visitors’ interactions with each bot action.
  • Scripting: In reality, chatbot scripting falls under the development stage, but we shall discuss it as a separate entity for the sake of clarity. A chatbot script outlines conversations and messages written according to the user’s needs and options. Scripting usually starts by understanding the business process. Depending on the business process, areas that require additional support are figured out. Then questions a bot can answer to provide this range of support are also formed. Based on the potential user issues, you can go further to construct a narrative of adequate answers to those questions. The answers ought to be clear, consistent, and concise. They have to sound natural as with the human language, get delivered at paces intervals, say in between milliseconds, and vary in response to a given question. For scripting tasks, professional copywriters are often invited because the tone, jokes, and communication style of the bot directly affect the user experience.
  • Analysis, training, and update: Once the chatbot starts working, the company has to do a proper analysis of its performance. The bot has to be updated regularly; this involves changing the conversation flows and responses based on regular data analysis. Vital factors for analyzing the chatbot success rate could be the total number of its users, the total number of user interactions, the number of interactions that led to service provision. The rate of human withdrawal or the software crash rate, the user satisfaction rate, and of course revenue growth can also be interpreted.

In a nutshell, if you have decided to build a chatbot from scratch, the first thing you should do is to define and divide the potential conversational flow into various outcomes. These outcomes are your company's’ services.

You might have to draw a basic flow diagram. Define the various questions and answers that will be used to obtain important information. With this data, your team of software developers can easily program your chatbot.

Know your users and their various channels of interaction with your product. Take into account the personality given to the chatbot, and continuously upgrade the bot based on available information.

Need a guide on your chatbot development journey? Find out how our experts and services can get you where you want to go, faster.

Technology Stacks And The Most Popular Development Platforms You Need to Create Your First Chatbot

Building a chatbot from scratch requires the use of programming languages such as NodeJS, Ruby, or Python. Although there are other programming languages like Java that can be used to develop a bot, they lack the support of most platforms. At this point, you have to understand two concepts: NLP and Machine Learning.

NLP (Natural Language Processing)

This is a branch of artificial intelligence that would allow you to create a chatbot that is capable of understanding what is meant by human users who express themselves in natural language (that is, as two humans would communicate) and, based on this, be able to formulate an answer.

An NLP system can be programmed manually (with a complex set of rules created by hand), but its true power starts when we introduce Machine Learning.

Machine Learning

This is another branch of artificial intelligence consisting of the development of techniques that allow machines to learn autonomously and automatically.

Among the Artificial Intelligence tools applied to the world of chatbots, possibly the most popular is Watson from IBM. Still, there are other alternatives such as Lex from Amazon, Luis from Microsoft, wit.ai from Facebook, api.ai from Google, or MindMeId from Cisco.

Many messaging and communication applications provide a set of libraries and resources, free of charge, that help developers to create chatbots that will work on their channels. Such is the case of Facebook Messenger, Slack, Telegram, or Kik. Microsoft also has its framework that allows you to develop chatbots that can work on the main channels.

You can also resort to unofficial platforms like Botkit, ChatScript, Meya, Gupshup, or Pandorabots. In this case, some solutions are free, but others are to be paid for.

In case you do not want to get involved in coding/programming, there are commercial platforms that allow users to create their chatbots from scratch at low prices. That does sound good! But keep in mind that such kind of ready solutions has a number of limitations, for example, it is difficult to build chatbots exactly to your business processes.

In many of these commercial platforms, although you do not have to throw in any code, it is possible to encode your custom properties into their own. This works when you want to completely change certain parts of the chatbots’ architecture and functionalities.

Some examples of commercial platforms are Botsify, Flow XO, Rebotify, Morph.ai, Motion AI, or Smooch.

There is another tech stack possibility: buy a predefined chatbot template that you can later customize. This is quite similar to commercial platforms. You can find chatbot template shops at BotMakers or Bot Store.

Depending on your choice, the development platform may not direct you on how to integrate your chatbot with the environment where you want it to function, such as your website or a messaging app. There is also a possibility that the integration alone is facilitated by paying either a fixed fee or a variable fee per use.

To avoid either of these two cases, some tools can freely integrate your chatbot where you want it to reside. Such as Recast.ai Bot Connector, which has broad compatibility, as well as being open source.

Pros and Cons

As you can see, there are many possibilities when building chatbots. It is obvious that without professional help from software developers, you will most likely muddle up your bots’ functionalities. Even though you may go through development platforms that claim not to require technical know-how to integrate, you still may be unable to build something bespoke.

If you deploy a chatbot whose functionalities are misplaced, you will drive customers away, because no one enjoys beating around the bush with a faulty machine.

Imagine entering a website and interacting with a chatbot that continues asking you «choose a shirt size?» over and over again even when you answer correctly. You’ll simply seek for other online shops that sell the same type of shirt, or you’ll close the faulty chatbot if there’s a «close» button.

Internet users in the US admitted to limited human interaction as the #1 challenge in using a chatbot ― Chatbot report 2019.

Challenges Of Using Chatbots

Source: Helpshift — showing the top challenges Americans face while interacting with robots.

This problem shows that chatbot systems even now are still far from perfect. Hence, we recommend that our developers test each of the available platforms, to see which one works best and suits the needs and requirements of your business.

On the brighter side, bots have and will continue to change the way machines and humans interact. Their predictability rate, considering what people might ask for or want, will continue to increase. According to a study Drift, 27% of American adults are willing to buy basic goods through a chatbot, and about 13% have purchased an expensive item before.

By lowering expenses and providing a personalized AI-driven interaction with their users, chatbots are increasingly becoming the new face of brands. Instead of paying human representatives to interact with users' live, it’s way cheaper to build a chatbot, which will ensure that every interaction is directed towards user assistance and satisfaction.

Developed to closely imitate how a human being would respond as an interaction partner, chatbot systems generally require periodic and constant analysis and upgrades. Bear in mind that your business goals always go beyond the chatbots design, and not the other way around.

The chatbot must generate profitable revenue for the company and its objectives. It does not become an innovation tech toy whereby the investment to build the chatbot may have no return under any framework.

Feeling inspired? See digital development solutions to get started with.

To Sum up

Every interaction with a customer is a chance to change their opinion about your business. Robots are great tools to ensure this. Most importantly, flawless performance and hyper-efficiency are a must when choosing to build and implement chatbot systems.

Developers at HuskyJam make sure the entire developmental process is as rigorous and impactful as it is successful. We not only seek to develop interactable systems for our clients, but we also follow the necessary steps of thoroughly testing designed software to provide and assure the optimal quality of operations.

What’s more, while developing these chatbots, we use advanced custom AI and ML-based tools to create and integrate smart configurations that will necessarily cater to your business needs. The result of which is a build that intuitively communicates and engages with customers on all channels.

We strive to meet your requirements at all times and will gladly walk you through every stage of the journey. After all, consumers need their money’s worth, and your business needs strong representation; the first impression of your business matters too. If a chatbot is the best means of improving customers’ experiences, then it should be rightly built.

Here’s a snippet of how you can leverage our AI-based and Machine Learning chatbot development services

  • Smart Chatbot: Design of language based on personality development of chatbots on Instant Messages, Web, and in-app.
  • Business Automation: optimizing and automating human work with the ultimate goal of improving service delivery at largely minimal costs.
  • Natural Language Processing: text recognition, identification of semantics, and creation of texts in the most human way.
  • Multichannel Conversation Management: development of high-quality conversational platforms for automating chats and creating the personalized user experience.

If you’re ready to start your next project or want to learn about different digital development which you can employ to your organization’s portfolio, reach out to us for a simple, cost-free estimate.

Subscribe to our newsletter

Types of CRM Systems
prev post4 Types of CRM: In-Depth Guide
next postHow to Find and Hire Python Development Company: Full Guideline
Python Development Team
0 commentsSign in to leave a comment