[24]7.ai has added advanced conversational capabilities for its artificial inelligence-powered virtual agent AIVA, as well as an improved modeling workbench for the agent and new visualization capabilities for its Customer Journey Analytics solution.
The advanced conversational capabilities aim to imbue AIVA with emotional intelligence, which [24]7.ai defines as "the ability to detect user emotion during interactions, acknowledge it, and respond empathetically."
"What we've done with AIVA, and what we've learned from many of our deployments, is that there are certain nuances when customers get frustrated…things like "see my comments above" or "are you insane?". If you're going to have a bot be your frontline, if that bot can't respond in a way that's empathetic and know when and how to transfer over to a live agent, it can make that entire interaction completely negative, and that's ultimately where a lot of bots are failing today," explains Angela Sanfilippo, senior director of product marketing at [24]7.ai.
"The differentiator here for us is, based on the dialogue and the multiple algorithms that are running on the side to detect emotion, AIVA takes a proactive stance when emotions start to rise and responds accordingly," adds Andrew Neff, senior product marketing manager at [24]7.ai.
The improved modeling workbench for AIVA reveals the AI behind the solution to end users, providing them with self-serve options. It includes a new graphical user interface that allows users to build and test conversation models and features technical capabilities that incorporate machine learning to proactively suggest improvements to intent models.
"Modeling workbench has the capabilities for our customers to adapt and tune and even test the models. What we've added in this version is the ability to actually see and edit and test the models," Sanfilippo says.
As for the new visualization capabilities for Customer Journey Analytics, they include a Single Customer Journey Viewer that aims to provide a consolidated view of customer engagement, including interactions across channels and transactions across systems. "We have the unique ability to combine data across every channel, voice channels included…into a single view. That's what we use to better understand how customers are engaging with customers, what are some of the root causes of any issues that may arise, as well as what are the root causes of positive outcomes," Sanfilippo says.