Sramana Mitra: I’m a little bit confused. You started off saying that the focus of the company was on customer experience. Now you’re talking about employee experience.
Christopher Connolly: We have multiple different stacks within Genesys. We’ve got 110 different products. They’re summarized into 11 different solution areas. We’ve categorized them into three top-line items. One is customer engagement. The other is employee engagement and the third is business optimization. All of our products are inside each of those categorizations.
On one hand when we talk about customer engagement, it’s about that customer edge. We have a collection of different products and services around employees. Connecting that customer with an employee means that we’re on both sides of that equation. Our business optimization category includes things like analytics and using AI in that to further optimize things like interactions and transactions that may not even have a human involved in the process.
Sramana Mitra: Double-click down on how you’re using AI in the customer engagement process.
Christopher Connolly: The obvious example there is chatbots.
Sramana Mitra: This is an automated chat experience that you offer to your customers. Your customers are using your live chat bot to interface with customers.
Christopher Connolly: Yes, that extends into voice as well so you can talk to the bots. We have what we call micro-apps, which are small embeddable apps that can be pushed via a different channel. Those apps do one very defined thing. You can assemble them and mash those together to deliver an experience.
In some parts, it uses machine learning for things like text analytics. We might be able to predict and use machine learning in a different way to predict what application you should interact with next to solve your problem based on what we know about you.
Sramana Mitra: This is a crowded space. It’s actually a crowded space not just today with AI being so hot. This particular space has been a crowded space for a long time. This is not a new concept. What is new here?
Christopher Connolly: I completely agree with you. There have been improvements along the way. I’ll give you a concrete example. For many years, when we think about connecting a customer to an employee, it was being built on business rules. Someone has sat down and thought about those business rules ahead of time. If you were trying to get in contact with Bank of America and you’ve gone through the chat bot experience and it didn’t help you. You want something that the chat bot was never trained for.
For 99% of organizations, someone has thought about that business logic to get you from live chat to a human or phone call to a human. What is changing now is that we’re using machine learning to take out the decision process of those business rules and let algorithms learn what path you should go on next.