Provide a Better Customer Experience with a FAQ Chatbot
If you still see chatbot as an instant marketing hit which helps achieve exponential fan growth in a flash, you surely need to catch up with the digital world. People have been starting to explore and execute chatbot’s richer functionality to deliver a smoother customer experience. A common use case across industries is FAQ.
Question and Answer
Questions displayed in a list view aid user navigation with clear UI/UX and graphical illustrations. Users are able to browse through the list and click for answers. Remember not to swamp your users with an excessively long list that shows all the FAQs straight away! Here’s a little tip for you: show at most 10 questions that are always asked and put a “More Questions” button underneath the list so users could continue to read the long list just in case they are interested to do so.
Apart from displaying questions in list view, chatbot can also process user input and identify different keywords to provide the appropriate answer. Whenever users input messages that match with any predefined keyword, chatbot will then reply with the corresponding answer. This approach guarantees chatbot a higher accuracy in answering correctly. However, the requisite to input the exact match of keyword may be a disadvantage in some scenarios.
Natural Language Processing (NLP)
To eliminate the possible incapability of chatbot to provide answers because users fail to input exact keywords, we will suggest you incorporate NLP into your chatbot. NLP uses machine learning to analyze and understand user expressions so as to respond with the correct answer. There are various third-party NLP engines in the market to help provide such artificial intelligence to chatbots, such as Google Dialogflow and Microsoft LUIS. You may even consider adopting engines developed by local startups. Both startups and big players have their competitive edge on analyzing human discourse under different context.
Nevertheless, one must be aware that the level of intelligence is highly affected by the amount of training data provided to the engine. The more you train, the smarter your chatbot will be. It is a continuous development that needs constant training effort. *Our chatbot builder solutions “Stella” has fully integrated with Google Dialogflow on providing the functionality of NLP to your chatbots, read more at here!
Originally published at Sanuker website