Chatbot…or anger machine? Customers are at the heart of every business. There is nothing more frustrating for the average customer than having to navigate some company’s automated support and messaging system. When each process “has to be” funneled through an AI empowered chatbot, to customer service representatives, all while distinctly feeling herded and managed, […]
It’s almost ubiquitous. At this point, who hasn’t seen one of the terminator movies? The plot is intriguing–creations beyond our control springing to life and threatening our very existence. The action is great, the special effects phenomenal (at least for its time) and there are some compelling moments that inspire deep thought. But we have […]
V.E.R.N.’s new dashboard is coming soon, but you can check out a preview here! In our latest video, we have walked through the dashboard system to show you how you can use V.E.R.N.’s API to detect emotions in your clients’ messages. On the home page of the dashboard, you can: See the trend line for […]
Recently we have interacted with a few organizations on social media, and have been approached by several chatbots to start a customer service interaction. Chat bots are autonomous programs that you may have encountered during a customer service experience, on your phone or online. They are software programs that either have a structured path of […]
Our newest emotion that we’re testing is anger. Here we have a demonstration of the early anger detector as it works through a few common scenarios: Passive aggressive, violent, bullying, customer service and more.
We decided the best way to explain how V.E.R.N. would work, we’d show how V.E.R.N. could be used in a real world scenario. Check out our classic customer service scenario between a live representative and a sarcastic customer. The analysis is only on the receiver (CSR) side, for obvious reasons but can be added to […]
We’re pleased to announce that V.E.R.N. (TM) is having great success in determining humor versus what is not humor. In this video, we demonstrate the effectiveness of the software as we drop humor and non-humorous messages into the analysis.