Using Machine Learning to build smarter chatbots

It’s common nowadays that we are observing more and more chatbots in the websites. Chatbots have saved up a lot of time for customers to solve their query in just a minute.

But sometimes, it can be very difficult for chatbots to understand every text which users provide. Machine learning ensures that chatbots become smarter and respond accordingly to the text. But, how Chatbots become smarter with Machine Learning?

How chatbots work

Chatbots are virtual users that simulate a conversation with another human. They are able to find a suitable answer to the questions of customer instantly and send it to them. Chatbot works very similar to human operated help desk software. It provides an answer to the question of the customer using Intent. Intent which is picked up by the chatbot is associated with a set of responses. These responses vary from different intent which bot picks up and send it to the customer. By avoiding the same responses again and again, chatbots provides the user a feel of the real human conversation.

Chatbots will never become smarter if they will not understand what actually the user is seeking. If they manage to respond in an accurate manner and provide the suitable answer to the query of a customer, then it might become smarter. But, without the help of AI and Machine Learning, it is impossible for chatbots to become smarter and act instantly with higher precision. Chatbots become smarter and intelligent as they learn and improve themselves.

When is a chatbot called smarter?

A smart chatbot understands and acts appropriately to the customer’s request. They aren’t smart by default. They are made smarter with the use of AI and Machine Learning. A chatbot will be considered smarter when:

• They have a proper understanding of the context in which users have requested. Determining the context in a statement is a typical task to automate as real human communication. To understand context more deeply, chatbot needs to analyze several aspects such as time, day, data, tone, conversation history or sentence structure. Smarter chatbots will analyze and understand the context of the conversation more precisely.
• A chatbot can easily interpret the context and based on that context it chooses an appropriate response. Generating a coherent response relevant to the query is a smarter and challenging task for the chatbot. Chatbot analyzes the intent of the sentence and picks up a response associated with that intent.
• The customer is satisfied with the service of the chatbot when it is more like a real human communication. The style and tone of the bot need to be consistent, just like a real human and it should not be in a different language or accents. This way of communication is really effective and satisfying for the customers.
• The chatbot will have the ability to learn from experiences. It will not ask the same question every time when a customer tries to communicate. Human has a habit of continuing the conversation where they last left off so it is mandatory for a smarter chatbot to not break the flow of conversation. Smarter chatbot will learn and improve its way of conversation with the customers. Also, it will improve its performance and responses with the ability of learning.

Make your chatbot smarter with ML

ML is a branch of Artificial Intelligence which is based on an idea that a machine should learn and improve itself through experiences. The machine uses a set of algorithms and patterns to function. Via ML, this algorithm and pattern can make better decisions without any human effort. The integration of ML in chatbots is to make them improve on its own and act accordingly to the situation. Chatbot consists of modules which can perform better by understanding and learning. Through ML, the learning capabilities of these modules are enabled which ensures, the chatbot becomes a good learner. The ability to learn is a key factor in creating a smarter chatbot. As the chatbot will learn from the conversations with the users, it will continue to grow smarter and smarter with each conversation.

With the integration of ML in chatbots, they are able to sense, think and act accordingly. It’s a three-step process to achieve a goal of becoming a smart chatbot.

• Ability to Sense: With the use of ML in chatbot, it becomes easier for them to sense the environment of the conversation. They simply interpret the information which is needed to perform a task. It also becomes easier for the chatbot to exactly understand the request of the customer. It becomes a challenge for the developer to infuse the ability to sense in the chatbot, however, ML has surely uplifted this challenge and enable the capability of the chatbot to sense the tone, sentence structure, accent, conversation meaning or its history to provide a better result to the customers
• Ability to Think: In simple terms, chatbot should be able to think what to do next when a customer places his request. The chatbot needs to access the information which user has provided and convert it into the useful and understandable format, then store it to its knowledgeable location. Via ML, chatbot easily embraces its pre-existing knowledge and uses it for the better responses to the requests. To enable the ability of thinking in chatbot, Neural Network in ML is used. Neural Network is inspired by the way human nervous systems functions. The neural network helps in processing the information for the machine and with the help of this network, chatbots are able to process the request of the users and respond appropriately. All the information and knowledge which is stored in their knowledgeable location influences the capability of the chatbots to learn more from their conversations with users.
  This capability will help to provide a response that is relevant to the request of the customer. Also, they can predict the conversation and plan ahead for the queries which might come from the users.
• Ability to Act: The chatbots should know when and what to respond. Thus, with the learning and understanding capability of the chatbots with the use of machine learning, it will help in generating a relevant response. Chatbots need to act accordingly with the request of users and type out a specific reply to a specific query. Typing a reply is generally easier for chatbot than responding via audio.

Does your website need a chatbot or you already have a chatbot but need to make it smarter? Get in touch.