How to Build an AI Chatbot?

how to build ai chatbot

Chatbots are the future of business communication. The new generation of chatbots powered by artificial intelligence is transforming the way businesses interact with their customers. They’re helping companies improve customer support, gain meaningful customer insights, automate repetitive tasks, and make other customer-centric aspects of their business workflow more efficient while saving time and money.

The adoption of AI-powered chatbots is gaining steam across industries, including eCommerce, media and entertainment, education, travel, and finance. This rising popularity of chatbots is also a result of customers’ preference for an instant, 24/7 support. According to a joint study by IBM and NRF, 76% GenZers consider responsiveness as a sign of a brand’s authenticity. 

With continuous innovations happening in the realm of artificial intelligence, it’s a great idea to develop an AI chatbot custom-made for your business. And the good news is that you can easily build a chatbot from scratch using the steps we’ve covered here.

Why do you need to build a chatbot?

A study on conversational AI platforms conducted by Accenture found that 57% of businesses believe chatbots deliver great ROI with minimal investment and effort. Chatbots are a great addition to your company’s business strategy, especially if it involves communicating with current or prospective customers. The multi-purpose role they play in both customer support and lead generation makes them an inevitable part of any business. Some of the reasons why you need to build an AI chatbot for your business are evident from the proven benefits they offer, including the following:

1. Chatbots enable you to offer 24/7 support to your customers.

2. Their self-serve functionality empowers your website, visitors, to quickly find solutions to their queries.

3. They reduce the load on your customer support agents and, therefore, decrease the support costs you incur.

4. Chatbots can direct your current and prospective customers to relevant campaigns and offers based on their preferences, thereby increasing your conversion rate and maximizing your sales potential.

5. AI-powered chatbots can have real-time conversations and ensure your users get only the best customer experience.

6. Interactions between your chatbot and your target audience can give you valuable insights and data to improve your business offerings.

Prerequisites for making a chatbot

Now that you’re convinced that you need an AI-powered chatbot for your business, there’s some groundwork to be done before you get to the step-by-step guide on how to build a chatbot. A chatbot is an invaluable asset for your business, and knowing the prerequisites for making a chatbot will help you get the most out of your investment. Let’s dive head-down into it!

1. Knowing what type of chatbot your business needs:

Do you need a customer service chatbot to help your users with their queries or a lead generation chatbot to increase your business’s conversion rate? Or do you need a multi-purpose chatbot that can handle both of these tasks as and when needed?

2. Determining the KPIs of your chatbot:

What do you want to achieve with your chatbot? Outlining the KPIs of your chatbot even before you start to build your chatbot will help you measure its effectiveness with the data points that matter to your business. These indicators could be anything from the number of link clicks or forms completed to the number of completed transactions.

3. Aligning the chatbot to your customers’ needs:

A successful chatbot must have a defined user persona to align with the target audience. But how do you create a chatbot user persona? The answer to this question lies in the following questions:

a) What kind of a user will be using your chatbot?

b) What is that user’s goal when they communicate with the bot?

c) How does your bot help that user?

Creating the chatbot user persona will help you address your customers’ pain points and also build the use cases for your customized AI chatbot.

4. Defining the platforms where you want to integrate your chatbot:

Do you want a chatbot for your website or app? Or do you want to deploy it on messaging platforms like WhatsApp, Facebook Messenger, Telegram, Kik, etc.? AI-powered chatbots are flexible, so you can integrate them with any of your preferred communication channels.

5. Giving the chatbot a personality:

What terminology and tone of voice will your chatbot use? Your chatbot is your company’s representative, so giving it a personality that aligns with your user persona will ensure maximum customer satisfaction. You can consider some of these factors to give your bot a personality:

a) a creative or eas- to-remember name

b) a friendly avatar

c) casual or formal language based on your industry

d) appropriate emojis  

e) ability to use images or gifs with text 

How to build AI chatbot from scratch?

Now that we have the prerequisites of creating a chatbot out of the way, let’s get straight to the steps for building a chatbot from scratch.

1. Choose a chatbot platform

The first step to creating a chatbot is to choose between two options: AI frameworks or chatbot platforms. AI chatbot frameworks act as libraries for creating chatbots by coding. Some of the common AI frameworks that software developers use to create bots include Microsoft Bot, IBM Watson, and Google’s Dialogflow. On the other hand, if you use a chatbot platform, such as DeepConverse, you get the building blocks to make your own chatbot quickly without any coding. Sign up with the platform provider, log in, and you’re ready to start building a chatbot.

2. Design a conversation flow in a chatbot editor

This step needs some visualization. What should your chatbot’s interaction with your customers look like? Start by coming up with all the possible questions or issues your users are likely to need help with. Using this data, organize the conversation based on predefined intents (like greetings, goodbyes, agent handovers, etc.) or custom intents (with domain-specific words). On the DeepConverse bot builder dashboard, you can drag and drop the building blocks to create a sequence for either type of intent.

Depending on the intent, the response can either be a simple response (answer) or a multi-step response (flow). Simple responses are quick answers to customers’ questions, for example telling them about discounts, helping them with help center numbers, or registration links. However, when the response to a customer’s question requires the bot to ask a question and then act on it, use the conversation flow builder on the dashboard to create multi-step responses.

3. Preview and test your chatbot

This is a step you should never miss testing your chatbot soon after creating it. Click the Test Bot button on the dashboard to preview it and check if everything works the way it should. Also, check all input options and all the possible variations of responses that you’ve set for your chatbot’s conversation flow and follow the path until the end to ensure everything is smooth sailing. If something doesn’t look right, you can go back to the bot editor dashboard to make the changes.

4. Publish the chatbot

Once you’ve tested your chatbot, it’s time to deploy it for the world to see and experience. Hit the Publish button once you’ve added all the required intents and their corresponding responses, and also whenever you add new data to an existing intent (this helps improve the recognition of that intent).

5. Train your chatbot

To train your bot, analyze the conversations and interactions between your chatbot and users to find frequently asked questions and the most popular queries. This data is available on the Conversations button on the DeepConverse bot builder dashboard. You can then add these words and phrases to create new intents or add them to existing ones.

6. Monitor, measure, and optimize

Monitor your chatbot activity regularly to find out what is working and what isn’t working well for your users. Analyze your chatbot data to measure if it is meeting the KPIs you had set before you even started to make a chatbot. Some metrics that you can track to measure its performance include chatbot activity (if it’s being used frequently), bounce rate (to find out how many users drop off without taking any or the desired action), goal completion (how many users reached the end of the path), and effectiveness (how many users got the help they needed). Based on this data, you can optimize your content and improve your chatbot. 

Features available in AI-powered chatbots

AI-powered chatbots, especially the ones developed by DeepConverse, have a host of features that make them a great addition to your business workflow. Some of the key features available in AI-enabled chatbots are as follows: 

1. User identity verification: This feature allows the chatbot to prevent user impersonation and ensure that chats are private. It enables the bot to verify all the user metadata before using it throughout the conversation flow.

2. Sentiment analysis: A feature that makes your chatbot more human-like, the sentiment analysis functionality allows your bot to understand users’ state of mind by analyzing their text/voice input. The chatbot can accordingly steer the conversation in the right direction and deliver a relevant response.

3. Announcement feature: With this feature, you can display anything from important messages or updates, ad campaigns, and/or promotions on top of the chatbot.

4. Business email checker: This feature enables you to identify and validate whether the email being used is business email or free email.

5. Calendly integration: Whether you want to schedule a meeting or an event, you can do that using your DeepConverse chatbot, which can easily integrate with the calendly app.

Tips for developing successful chatbots

To ensure your chatbot is built for success, there are a few handy tips you can check off while creating one for your business. The tips are as follows:

1. A human touch is a must:

It’s all in the personality! This is one of the most important factors that separates successful chatbots from not-so-successful ones. In his research, Stanford University professor Clifford Nass found that interaction with robots activated the same areas of the brain as communication with a fellow human. Customers tend to build a positive association with brands whose chatbots have quick-witted, “human-like” responses. To start with, give a friendly name to your chatbot, then add a unique tone of voice that suits your target audience, and there you have a bot with a personality.

2. Simulate a real human conversation:

The flow of conversation between the chatbot and the customer should be as natural as possible. For a natural flow, the chatbot should split long answers into batches of quick replies with an appropriate delay between messages instead of sending big blocks of text. This ability to closely mimic written/spoken human speech adds a human element to chatbots that drive them toward success.

3. Transfer complex queries to human customer support agents:

While chatbots are programmed to be adept at resolving small issues, often, there are instances where human intervention is required for more complex issues. In such cases, the chatbot should be able to seamlessly hand over the conversation to customer support agents. Also, some people (36%, as per a study) prefer to talk to an agent instead of chatting to a bot, irrespective of the complexity of their queries. You should design your chatbot’s conversation flow in such a way that the option to talk to a human agent is always there.

4. Avoid designing dead-end conversations:

Customers should always be able to take action with the answers the chatbot offers. They should also be able to restart a conversation even after it’s over. So when you’re designing your chatbot’s conversation flow, identify and fix dead ends to ensure a great user experience.

5. Don’t overcomplicate conversation flows:

Branching into too many flows in an effort to make the chatbot more interactive will make it hard to manage. Keep the conversation flow as simple as possible to keep the number of messages low, thereby making it easier for you to analyze them.

6. Avoid allowing extremely open-intent conversations:

The outcome of every conversation your chatbot has with your customers should be precise and relevant to the question. While simulating human conversation with quick-witted answers is key for a pleasing personality, overdoing it can lead the bot to digress from its main job guiding users in the right direction.

Suggested read: Top 10 AI Chatbots for Customer Service


Do you think your business and your customers will benefit from having an intelligent chatbot on your team? Test out these steps with the DeepConverse bot builder to design your first bot. For assistance, get in touch with us.


Q.1 Do I need any tech skills to make a chatbot?

A. When you use the DeepConverse bot builder, you do now need any tech skills to make a chatbot.

Q.2 Are chatbots effective?

A. Yes, chatbots are some of the most effective tools for business communication. One of the most notable use cases where chatbots stand out is 24/7 customer support. Customers can easily and effectively use a chatbot for getting quick answers to their queries, resolving complaints, getting detailed explanations when required, making reservations, paying bills, making online purchases, and more.

Q.3 Why do chatbots not work or fail in some scenarios?

A. It depends on how the chatbot was built, its capabilities, and how you use it. Some of the common reasons that can lead to a chatbot failure include having an unclear scope of utilization with vague goals, lacking customer perspective, bad design (first impression matters in the case of chatbots too!), or not integrating the bot with the right communication channel or workflow. A chatbot can also fail when it is not programmed to tackle all possible scenarios or when it is launched before it’s ready this is why testing your chatbot before deploying it is very important.

Q. Is chatbot AI or ML?

A. A chatbot can be either AI or ML, neither AI nor ML, and it can be both it it depends on how the bot is built and the use cases it is applied to. There are rule-based chatbots that don’t use either AI or ML and depend exclusively on a database of questions and respective answers. Then there are conversational AI chatbots that are developed using artificial intelligence, machine learning, and natural language processing (NLP) technologies to make and customize algorithms that make them capable of performing intelligent functions, such as sentiment analysis, fraud detection, keyword analysis, and having real-time human-like conversations.

Q.5 What is the cost of building a chatbot?

A. The cost of building a chatbot depends on the precise nature of the requirement. Get in touch with us for details.

Q.6 How much time do we need to create a chatbot?

A. The time needed to create a chatbot depends on how much customization it requires. It can range anywhere from 5 minutes to one hour.

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