How To Train AI Chatbot

With the rising importance and recognition of artificial intelligence, the customer support industry is moving rapidly towards the indispensable tool, called an AI chatbot, to improve customer service and satisfaction and generate more leads. Now, the question arises- how can one create a smart and responsive chatbot? The answer is, by training it. Training a chatbot is a process made easy with various no code solutions available such as Appy Pie’s Chatbot Builder. Let’s dive in to know more about it.

What is an AI Chatbot?

First things first, let us understand what a chatbot is. In layman’s language, it can be defined as a computer program that interacts with humans. But a chatbot has much more meaning to it when it comes to deploying it on a website or an application.

AN AI chatbot is a bot designed to converse with humans, answer their queries, and handle customer relationship management. It’s not this smart on its own, you’ve got to train it. Chatbots can go from being equipped to answer only simple queries, to being complex structures with a vast database. Nonetheless, they are a very important part of your CRM structure and their significance is growing rapidly in the digital world.

Earlier, developing chatbots required a deep understanding of code. A chatbot’s primary motivators were decision trees and preset rules. However, this limited the bot’s flexibility because it lacked a sophisticated database to comprehend and reply to intricate inquiries.

With the advent of major technological developments like AI and NLP (Natural Language Processing) which are the major building blocks of a chatbot, little coding skills are required to build a chatbot. That is correct. These days, you can create and train an AI chatbot from scratch without knowing any code thanks to several no-code chatbot programs like the Appy Pie Chatbot Builder.

The Importance of Training an AI Chatbot

Why is training a chatbot important? The first and foremost reason would be to help it understand, analyze and respond to a plethora of diverse user inputs. When trained, a chatbot easily comprehends what a user types in, and accesses its database to give an appropriate response. This helps streamline customer relationship management processes which improves user experience.

Another important reason for training your chatbot is that it keeps learning around the clock and can access data from past conversations to give more relevant responses. Furthermore, adequate training given to a chatbot on a large database of phrases and entities guides it to generate valid answers and actions. Training a chatbot also helps in cost saving, due to the little human help required. They ensure reliability and precision in responses, thus creating a uniform customer support structure and providing satisfaction to customers in meeting their requirements.

All in all, training a chatbot well should be the utmost priority before deploying it on your website by making use of the convenient no-code solutions available.

How to Train an AI Chatbot in 7 Simple Steps?

Now that you have a basic idea of what a chatbot is and are familiar with related terms, let us go into the procedure of How to train an AI chatbot. Here are 7 easy steps you need to follow-

  1. Select your Bot

  2. Bot Selection Screen

    The first step in the process is to select the type of chatbot you want to deploy. Once you’ve logged to your account, select the type of chatbot to start with, be it a GPT-bot, inquiry bot, appointment bot or a customized bot to be created from scratch.

  3. Edit Bot Flow

  4. Bot Editor Screen

    Now, you will arrive on the bot editor screen. Edit and customize the bot flow according to your requirements, including a welcome message, feedback prompt, information retrieval message etc. to define the flow and structure of conversation.

  5. Add Handoff Node

  6. Add Handoff Node

    In the editor section, add a handoff node to define the ending point of a workflow and click on ‘Save Draft’. When the conversation ends and the handoff node is triggered by the user, it is transferred to another workflow like to a live agent or an email for further action by the user.

  7. Add Training Data
  8. Now, click on ‘Configure’ to reach the ‘add training data screen’ to feed data into the chatbot’s knowledge base and train it on that data. Here, you have two options-

    • One is to train your chatbot through adding data files. Add any file with information you want to feed into your AI bot’s database.

    • Add Training Data Screen
    • The other is to train it through adding a web URL. Add any web link that you want your chatbot to have access to and knowledge about the information it includes.

    Training with URL

    You can train your chatbot using a combination of both- training through files or training through web links.

  9. Complete the Training Process

  10. Bot Training Screen

    After uploading the training data into your bot’s knowledge base, the data will automatically be analyzed, prepared and the training process would be initialized. The chatbot is trained on the data, its responses are fine-tuned and the model’s performance is optimized. The chatbot is now ready for preview!

  11. Design and Customize

  12. Customize and Design Screen

    Click on the ‘Design Customization’ option on the screen and customize the AI bot’s widget, avatar, background, color, header etc. to determine the look and feel of your chatbot.

  13. Setup your Widget

  14. Widget Setup Screen

    The last step in the process is to set up the widget of your chatbot. Click on the ‘Setup’ option and you’ll find a widget code. Copy this code, paste it into the section of your website and reload the page. You will now see the fully functional widget of your trained AI chatbot appearing on your website.

Tips and Tricks for Training an AI Chatbot

If you want your chatbot to be on its A-game, you can keep some of these tips and tricks in mind while training it-

  1. Define Its Use Cases- Use cases of a chatbot can vary from business to business. It depends on what the users on your website want, for what queries they approach the conversational AI and what responses they are expecting from the chatbot. Some examples are order tracking, complaint redressal, policy information etc.
  2. Collect Relevant Data- Gather as much information as you can to include in the chatbot’s database; the more, the merrier. Having the right information and the right kind of data in the bot’s database is the key to making or breaking a good user experience. Chatbot data might include texts and transcriptions from emails, social media, websites and old customer support conversations. Also, make sure to keep revising phrases and entities guiding the bot to ensure that they are in line with the key intent of user input for the proper action to be delivered.
  3. Regular Testing- Continuously test your chatbot’s functioning via live agents or live chat software to discover loopholes and ensure to review conversation history from time to time. Monitor and track the chatbot’s performance analytics via online tools to maintain proper records of its working. This helps you remain updated on user interactions, roadblocks they face, solutions they expect etc. Some key performance indicators like use rate, bounce rate, response volume, session volume, conversation length, retention rate and activity volume can be analyzed to measure performance.
  4. Data Categorization-Using NLP tools, collected data should be grouped under different topics and intents using data categorization. For example, a school or educational institute can categorize data into heads like fees, curriculum, syllabus etc. This helps in easy recognition and understanding of the data by the chatbot.
  5. Crowdsourcing and Customisation- Customise the data fed in the chatbot’s database according to different languages. It’s important to keep the data multilingual using crowdsourcing to suit all users and enhance user experience. Another thing to keep in mind is the medium of response. A chatbot might be voice-based or text-based. Data needs to be incorporated according to the medium and the chatbot should be trained on accessing the correct information.
  6. Feedback Button- Always add a button in the chatbot to ask for the user’s feedback after a response has been provided by it. This can help discover the degree of user satisfaction, pain points in the bot’s functioning and the necessary changes that need to be incorporated in the database. The feedback is bifurcated into a negative, positive and neutral category which further makes it easier to store and use data.
  7. Keep Track of Conversations- You can enhance the chatbot’s performance by conducting a trial run and analyzing conversations between the users and the conversational AI bot. This can help you understand what hurdles a user faces while navigating through the site lags in the bot’s actions which require improvement. One should keep refining and adding different phrases in the chatbot’s database as and when they arise to make it resourceful and efficient.
  8. Determining User Intent- It is essential to feed in the chatbot’s database, the reasons due to which a particular question or user input arises. This is to help the bot in intent recognition. The chatbot should be aware of why a particular user input is written and what the user expects it to do. For instance, a user asks the bot for the return/refund policy. The chatbot’s database should be well-resourced with why the user would want this policy and what action should be taken by it.
  9. Tip: Make sure synonyms of a particular phrase in the user input lead to the same intent recognition result, like “I want to return a product” and “Return/Refund Policy” should prompt the same action by a chatbot. The keywords from various phrases would then form entities to guide the bot.

  10. Developing its Personality- No one wants to have boring conversations, even with a bot. Give your bot an interesting conversational style and feed humorous statements and a fun tone in its database to keep the users engaged while interacting. Another aspect of personality would be using various communication elements like textboxes, media, GIFs, buttons, drop-downs etc. for ease in putting forward a query. Lastly, incorporate color, designs and a good look and feel of the chatbot for a better user experience.

You can always incorporate more steps and tricks in your chatbot training journey depending on your site’s needs. These should be applied by all team members training the chatbot to avoid contradictions.

Also Read: How to Prepare a Customized Chatbot Flow using Appy Pie’s Chatbot Builder

Conclusion

In summary, there has been a significant evolution of the chatbot from being a simple rule-based structure to a now no-code AI-driven computer program that requires training to function properly with the use of Natural Language Processing and Machine Learning techniques. These can be easily applied by anyone who is not tech-savvy using no-code solutions provided by Appy Pie’s Chatbot Builder. The steps and strategies mentioned in this guide can help you revamp the way of Customer Relationship Management and help your company increase website visibility and engagement, gain goodwill and most importantly, earn loyal customers.


Page reviewed by: Abhinav Girdhar  | Last Updated on July 8th, 2024 1:28 pm