  In recent times, a large number of people have been involved in establishing
their own businesses. Unlike humans, chatbots can serve multiple customers at a
time, are available 24/7 and reply in less than a fraction of a second. Though
chatbots perform well in task-oriented activities, in most cases they fail to
understand personalized opinions, statements or even queries which later impact
the organization for poor service management. Lack of understanding
capabilities in bots disinterest humans to continue conversations with them.
Usually, chatbots give absurd responses when they are unable to interpret a
user's text accurately. Extracting the client reviews from conversations by
using chatbots, organizations can reduce the major gap of understanding between
the users and the chatbot and improve their quality of products and
services.Thus, in our research we incorporated all the key elements that are
necessary for a chatbot to analyse and understand an input text precisely and
accurately. We performed sentiment analysis, emotion detection, intent
classification and named-entity recognition using deep learning to develop
chatbots with humanistic understanding and intelligence. The efficiency of our
approach can be demonstrated accordingly by the detailed analysis.
