Businesses evolve, customer language changes, competition repositions, companies release new products and services. Business never stops. Because of this, conversational AI in the enterprise will always need a human’s input to learn new things.
Many call centre executives and managers in the enterprise struggle with a lack of visibility into the reasons customers contact a company for millions of customer interactions, and how typical contact-centre metrics look for those specific topics.
So you built a virtual agent for your website, and customers love it. Later on, you discover that your support team is getting too many customer inquiries from Facebook, so you decide to add a virtual agent to your Facebook page as well.
To prevent becoming just another statistic, there are a variety of precautions that can be taken to ensure your chatbot and Conversational AI strategy will succeed. Below, we explore some of the common mistakes companies make when deploying a chatbot, and how you can avoid them.
Many people wonder how Robotic Process Automation (RPA) differs from Conversational AI and Natural Language Processing (NLP).
The majority of B2C enterprises are now working on deploying Conversational AI products, for both internal and external facing use cases. With the relative immaturity
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