Chatbots utilize natural language processing (NLP) and speech recognition to understand written and spoken requests; businesses can leverage this technology to automate tasks that formerly required human intervention. Based on a request from a user, the chatbot provides the user with an output, which is a response to the request in text or speech form. With the use of machine learning and deep learning, chatbots can grow intelligently and understand a wider vocabulary and colloquial language, as well as provide more precise and correct responses to requests.
There is a lot of potential for using chatbots for marketing. For example, it is possible to use Facebook advertising to send users directly to a Messenger chatbot. Users interacting with the chatbot consent to be contacted by the bot at a later point in time. This means that the cost-per-acquisition of Messenger contacts can be much lower than traditional email marketing.
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1. The chatbot never sleeps: Customer service is all about convenience, which includes 24/7 customer support. A cost-efficient, yet powerful way to provide basic support is through the never-sleeping chatbot. Devine shared an excellent example of this. In the banking industry, Workfusion’s chatbots are trained by using historical conversations and can perform some of the same tasks as a live support center rep such as correcting an invoice, answering basic questions about account balances and more. Customers receive the same level of service they would get from the support rep. The chatbot can recognize human emotions such as anger, confusion, fear and joy. And, as mentioned above, if the chatbot detects that the customer is angry, upset or frustrated, it will seamlessly transfer the interaction to a human to take over and finish assisting the customer.
Fortunately, the next advancement in chatbot technology that can solve this problem is gaining steam — AI-powered chatbots. By leveraging machine learning and natural language processing, AI-powered chatbots can understand the intent behind your customers’ requests, account for each customer’s entire conversation history when it interacts with them, and respond to their questions in a natural, human way.
Rasa NLU & Core allows for more human-like dialogue, trained using interactive, and supervised machine learning. Rasa Core picks up patterns from real conversations and also takes the history and external context of a conversation into account. The Rasa NLU engine is an open source tool for intent classification and entity extraction, and offers natural language understanding for bots and assistants. It features the capability to turn natural language into structured data. It is modeled as a set of high level APIs for building your own language parser using existing NLP and ML libraries. Many developers world-wide are using it…

By collecting over 20 years of messaging transcript data and feeding it to their AI-powered chatbot, LivePerson can automate almost every industry’s messaging and integrate with most messaging channels like your website, mobile app, Apple Business Chat, text messaging, Google Rich Business messaging, Line, Facebook Messenger, WhatsApp, and Google AdLingo.

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Reply is one of the best AI chatbot platforms. It is an enterprise level bot-building and management platform. And it enables B2C communications at scale. Their visual bot builder makes it easy to build bots. The dashboard has built-in CRM, machine learning, and real-time insights to make smarter and faster bots. You can expand bot functionalities across the whole customer experience.

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