Enhanced User Experience? Think Chatbots

 


With the ability to fulfill any realistic wish of a user, Chatbot is a homogenous digital entity that can be well related to the Genie of Alladin.

You want to get service details of a web bot or you want some recommendations on a product for online purchase or if you wish to perform any other smart task from a chatbot, it is there to do justice to your command.

Whether serving as a web bot or running at the backend of a mobile application, chatbots have made their existence possible in all industry fields and work spheres where they have excelled in simulating human-like behavior.

A personalized chatbot:

  • Communicates through smart speakers
    • Work through popular messaging and chat platforms
      • Work efficiently on smart home devices
        • Connect with a customer through voice or text
          • Respond to customer requests promptly

            • Digital experiences and technological advancements aim at improving the lives of people and become increasingly demanding when it comes to leveraging user experiences. And reciprocate, user expectations have speeded up the development of technologies, thus, achieving a generalized impact on consumers.

            [Prefer Reading: “AI-Powered Chatbots: Enhancing Business Communication” ]

            Technologies Working behind a Chatbot

            When the talk is initiated about chatbots, Artificial Intelligence is a never-missed concept to be stated about. Artificial intelligence and machine learning and many of their descendants play a significant role in making a chatbot efficient to accomplish its tasks at scale.

            Artificial Intelligence is a deeply integrated technology that is capable of capturing huge volumes of relevant customer data. While there occurs a point where understanding deep and distinct user behavior and intent of the conversation becomes complex for AI algorithms.

            When the output is to be adjusted as per the right context of the input, all eyes look upon the robust concept of Natural Language Processing for chatbots.

            Modern chatbots used by big brands and leading companies incorporate advanced speech and natural language processing functions that allow them to decipher questions regardless of the tonal differences of their interlocutors, as well as to decode their intentions.

            Natural Language Processing applies the principle of deep learning that in the case of chatbots assesses the intent of the user input and creates pout based on the contextual form that is analogous to that of a human being response.

            How does NLP Work in a Chatbot?

            If a machine is to interpret the human message, it requires structured data to interpret the input which further includes extracting important and relevant information from the user message.

            This is done with the help of algorithms that are run to get meaning and context from every sentence to deduce data from it.

            How do Chatbots Intelligently do it?
            The essential segments of this data extraction are to distinguish the entities and the intent which helps a bot render possibly exact matches of the queries.

            The intent is the goal of the statement and an entity is something that modifies or supports the intent. The NLP model is built for every entity for any intent.

            Let’s analyze the Chatbot’s Process Break Down taking the scenario of making an Online Purchase:

            Let’s say if you choose a chatbot for making a decision on buying a product. When the input is given to the chatbot in the form of a message, it simply sends a plain text to the NLP engine.

            The NLP engine next converts the text into structured data for itself and various NLP models are used to extract the intents and entities for adequate extraction. Then the gathered data is taken to the decision-making engine.

            This decision-making model derives precise information based on the results and actions and then the chatbots convert the decision data to text. Further, using NLG, the message generator outputs the message. This message is presented to the user in the form of a text message or voice.

            “Organizations can reduce customer service expenses by up to 30% with virtual agents and chatbots. Mixing chatbots with human interaction is key to creating personalized and successful experiences.”

            [Prefer Reading: “How Natural Language Processing (NLP) Aids Sentiment Analysis?”]


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