Customers and employees expect fast and accurate answers to their questions. Unfortunately, too many chatbots misinterpret the ask if it’s not written in a specific way. The result is irrelevant answers, usually followed by a long, frustrating wait to talk with a live person. For companies trying to support an unprecedented number of customers and employees through digital channels, it’s time to elevate the conversation. It’s time for Smart Answers on Lucidworks Fusion.
Smart Answers makes existing chatbots smarter and better at resolving simple questions, delivering improved call deflection and providing faster triage and better prioritization. That frees your support and helpdesk agents to focus on the more complex and nuanced questions that represent a more valuable use of their time.
Chatbots are supposed to help customers help themselves, but most are rules-based and static—making customers guess the right question. Poor self-service frustrates customers with long wait times for manual support. Smart Answers makes self-service easy—improving customer loyalty and retention.
With many more of us working from home, remote employees need quick access to information. Smart Answers helps workers navigate corporate policies, resolve IT questions and serve customers by answering questions instantly.
Smart Answers is ready to go right out of the box—creating faster time to value. This “cold start” capability is achieved by training Smart Answers on existing public knowledge systems like Wikipedia, so it knows a lot before it ever sees your content. You don’t need a data scientist to set it up.
We conducted an A/B test where we introduced a self-solve based homepage to some customers. There was an increase in traffic that confirmed that customers are really motivated to self-solve and we saw a 7% decrease in support case creation for customers who were given the self-solve homepage.
Principal Software Engineer, Red Hat
Seamlessly connect to existing chatbots, virtual assistants, and voice applications.
Empower developers to train and implement machine learning models.
Interpret user intent and deliver relevant results, with or without FAQ docs.
Import custom models into your conversational applications.
Connect knowledge bases from any source to power deep learning.
Power conversational experiences with a human level of understanding.