How Apptread builds business intelligent-interactive chatbots?

How Apptread builds business intelligent-interactive chatbots?

The potential of chatbots is not lost in the enterprise world. Earlier, chatbots were only used to handle customer service operations for a business, but now organizations are exploring the hybrid versions in other functionalities as well. As brands are now focusing primarily on promoting personalized experiences, brands are getting involved in creating intelligent chatbots to connect with users. Nonetheless, it is hard to find a live intelligent chatbot, also called an AI chatbot. As the thought of an AI Chatbot comes into the mind of the users, they know for sure that it’s not a human-based experience. Although the businesses have been really innovative while creating the chatbots and hence, what we experience is that chatbots succeed in bringing the human touch. The essence is not primarily chatbot, but the intelligence of the chatbot that can bring the human touch.

Chatbots have existed for years but emerged as a powerful business tool recently. Businesses have started to exploit the opportunities with chatbots and started using them in most of the business functionalities, which gives them maximum returns. It is the intelligence that gives the ability to the AI chatbot to learn from conversations with the users and tackle every situation that comes it is away. As businesses explore the chatbots into complex territories, raising the intelligence quotient along with it becomes increasingly difficult. How to build smart chatbots which engage our users in current scenarios?

Understanding what our user’s want in a Chatbot

Chatbots, when created efficiently, are smart enough to understand what a customer needs. For example, a chatbot helping out a customer to book a doctor’s appointment. The users know which doctor they would like to visit, based on the ratings and requirements. Now the AI chatbot needs to understand this specific user needs to provide a relevant answer. An intelligent chatbot will understand and learn the language & tones to give a convincing solution. 

In the future, a time will come where all bots will be created using artificial intelligence and will know what the users want before they even ask it. To cut down build-up complications, it is important to ignore proactive user queries by keeping them local. An AI chatbot is rooted in the human capacity of self-learning and gaining information efficiently. Thus it’s crucial to make the chatbot sense natural language expressions.

What is the model of Intelligent Chatbot?

Most of the chatbots are developed on the retrieval-based model & work on the concept of predefined responses. For example, the chatbot picks up the relevant answers from the repository stored in the memory, based on the previous queries of the users. Generative models designed using machine translation approaches come with the ability to bring out new responses right every time. Generative models are promising in nature & enable longer conversations with the user where the chatbot deals with several queries. A chatbot built-in conversational AI platform lets you focus on building a bot experience that delivers to your users without worrying about the underlying capabilities or proximities.

Characteristics that define that a chatbot is intelligent:

The AI chatbot works autonomously while fixing a goal & achieving it. This is a difficult task itself, where the chatbot has to identify the goal in a specific situation. The chatbot takes on a three-step process for achieving the goal. It is the recognize-think-act cycle that can define how intelligent a chatbot is. An AI chatbot goes through this set cycle to achieve the pre-defined goals autonomously.

1.  Power to sense:

For an AI chatbot, sensing the habitat where it resides becomes an essential path for getting the details required to complete a task. The chatbot finds it easy to listen to what the user needs than make sense of what is being conveyed by the user. Take the instance of a robot that you want to put together. It becomes challenging to inbuilt the sensing power into a robot for there is a need to integrate the robot with the latest sensors.

2. Sharp to think:

The chatbot needs to think about what to do when a user places his request. The chatbot transforms the information received from the user into an intelligible format and stores it in a knowledge base. An AI chatbot decides by leveraging pre-existing information based on past conversations and one that continuously preferred queries. Based on the decision, the chatbot takes action to achieve pre-defined goals. Use neural networks in machine learning to prepare the chatbot to think and take actions depending on the query placed by the user. The knowledge base determines the learning capacity of the chatbot from its past contributions & interactions with all users. For instance, take the example of Siri and Google Now. Their intelligence is based on the knowledge stored internally. This knowledge base helps the chatbots in learning faster, identifying relevant solutions, and providing a relevant response.

3. Pro-active Action:

As the thought process gets over, the chatbot knows the action which is the most relevant ones in the given scenario & will sate the user’s query. Now, the chatbot needs to act fast. The chatbot types out the response to the query raised by the specific user. Typing out a sentence for the query raised is comparatively easier for a chatbot when compared to giving out an answer via audio or video capacities. For audio- or video-based chatbot, answering the user’s query through a suitable action becomes very difficult as it has to sound like a human.

Business operations & the Future of Chatbots

Chatbots, which are an integral part of businesses have been spotted in the past, but it wasn’t till internet usage became an important part of the user’s life, that the chatbots as we recognize them today, started as the customer support for the businesses. As technology emerges, customer support is performing via messaging apps & automated calls, there are growing numbers of use-cases where chatbot deployment gives organizations a substantial amount of return on investment.

According to the studies of understanding the user’s perspective, they find the chatbots very intuitive & innovative. For businesses, AI chatbots are leading ways to build and enhance ways of giving out the personalized and engaging customer experience, which in return delivers a pool of valuable customer insights that are treasured by an organization as they create a better understanding of their customers’ need which is essential for a business to grow into multi-folds.

Apptread enables businesses to conduct operations by building the best-suited chatbots. To know, how we can build and enable the chatbots that our clients love, connect with us at