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November 2, 2022 – Duration 00:25:43
Great CX employees want opportunities to learn new skills and advance their careers. And they want clear, consistent expectations. Delivering on those preferences can keep your employees engaged and motivated — and that increases your chances of retaining them. David Wasserman, Senior Director of Product Marketing for Workforce Engagement Management at Genesys, explains how technology can help. Using the science of empathy and human behavior, the right technology can help with timely feedback, positive reinforcement and guidance to keep employees engaged. The right nudge at the right moment motivates employees to take the best action, improve their performance and deliver on your brand’s promise.
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Senior Director of Product Marketing for Workforce Engagement Management
David joined Genesys in early 2022 as part of the Product Marketing organization, focused on Workforce Engagement and Employee Experience. His primary responsibilities are creating and delivering marketing programs on how the companies solutions enable organizations to transform their employee engagement strategies to attain market leadership.
Prior to Genesys, he held leadership roles at NICE, an AI HR-technology startup as well as telecommunication industry leader Verizon. His responsibilities included Product Marketing, Product Management and Sales. He is passionate about the role Marketing plays in articulating a firm’s value proposition in meeting customer and market needs.
David holds an undergraduate degree in Business and an MBA in Marketing.
Here are conversation highlights from this episode, edited and condensed. Go to the timestamps in the recording for the full comments.
David Wasserman (02:39):
Nudging is an approach that was popularized in around 2008 by Richard Thaler and Cass Sunstein. It’s about how we motivate people to do really what we need them to do. How we give them positive reinforcement and influence them in their decision-making process to more closely align what they want to do with what others may want them to do. Let me give you a parallel in life: When the sun comes up, it’s an immediate nudge to wake up and get our day started. If we walk into a kitchen and smell amazing food, we become hungry. So, it’s essentially taking that nature-driven process and applying it in business.
David Wasserman (03:51):
At Genesys, we call it the science of empathy — putting yourself in the shoes of the employee and understand how they think. How are they operating and how does that align with how we do business?
In some cases, maybe it doesn’t align. And from there you’d give folks what I call empathetic nudges. These are like subliminal cues that suggest that certain behaviors are necessary. If you think about a contact center handling thousands of interactions a day across a variety of employees, you’re giving them nudges or cues at particular moments in a customer interaction that causes them to do something that will result in a higher level of customer satisfaction.
David Wasserman (05:36):
When you think about “listening,” it’s recording interactions. It’s not new, but the learning part is new. What I mean by “learning” is examining the decision process and then taking action on what we’re understanding is happening. The customer said this, the agent did that, it satisfied the customer. It’s putting things in a process flow.
David Wasserman (06:42):
First, the technology that enables this is a speech and text analytics product. It listens to the interactions and is understanding or learning from those interactions. So, from a technology perspective, there’s no barrier.
The biggest challenge with this is, getting over old bias of “the way we to do things.” Typically, in a contact center, people are trying to learn from a small sampling of interactions. That usually results in maybe 2% to 3% of the interactions being listened to or reviewed.
And then, of course, there’s human bias. You have supervisors or managers performing this function, and the results are not only small samples, but they’re also biased samples. So, one of the biggest challenges in getting past where we are today is to use speech and text analytics to automate that process and eliminating the human bias.
David Wasserman (07:54):
Learning is different than understanding. Learning is “do this, get that.” Understanding is the why. That’s what’s most important. Understanding also comes through an advanced speech and text analytics product that’s layered in with artificial intelligence capable of giving you the why. Not just that someone did this and it resulted in that, but why was that even occurring to begin with? Why did the customer react that way? Why did the agent react that way?
When you combine the learning with the understanding, you’ve got the full package on what’s really going on, and from there you can implement nudging to try to adjust the result.
David Wasserman (09:21):
One of the benefits of implementing the approach of listening and learning is the ability to predict. You can take the next step because you understand the type of interaction that’s occurring. You can intercede because you know what the probability of an agent taking an action is, and you know the typical customer reaction. And, at least with the agent, you can adjust their behavior through nudging, through the UI, through some sort of knowledge management system that provides them additional information — and, in turn, that actually nudges the customer.
In the end, the goal is to take those two individuals and have them have a better match and a better interaction and a better outcome for both.
David Wasserman (10:17):
A very simple example is knowledge management. Customer service agents get asked an enormous amount of questions. Some they’ll know the answer to and others they won’t. The result of not knowing the answer without any sort of nudge to move you in the direction of providing the customer what they need is a frustrated agent, a frustrated customer, and a poor result for everyone involved.
Something as simple as helpful information that appears on the agent’s desktop to guide them to what they need versus them guessing or saying they don’t know the answer is an example of using knowledge management as a nudge.
David Wasserman (11:23):
Nudging, as I said at the beginning of the talk is kind of inherent in the way we all operate as humans in nature. For those companies that are interested in improving their CX in a significant way, they’ll look for capabilities that enable that. They’ll look for a UX design that’s attractive to agents; that’s guiding them through the call with those clues, versus them guessing all along the way — and it directs them to provide a better customer experience.
David Wasserman (12:34):
When I think about nudging, I think about how people have innate qualities. Not everyone is cut out to be a customer service agent. You’re looking for people that have an empathetic ear to a customer’s challenge. So, first, it’s about choosing the right people. But not everyone is as empathetic as needed in a particular situation. And that’s where making a UX that’s intuitive guides an agent to provide the service that the customer’s expecting.
Also, this idea of nudging cuts across every element of the contact center. It could be the quality management process, the workforce scheduling process, the performance management process, the ability to design a UX that’s not just user-friendly, but also nudges employees to do things that are closer to what the business wants and what customers want.
David Wasserman (14:13):
For the UX designers and technologists, it’s about having a human element in their design. It’s not just about that the technology can do something amazing or that the screen looks great, it’s about helping agents do their job. That’s what you’re looking for.
And it doesn’t occur all the time. In some cases in the technology world, we do things because it’s amazing that we can do them, but they don’t have a great benefit for the humans that are involved in the process.
David Wasserman (15:43):
AI is making humans smarter. It’s letting humans focus on the complex things while the AI does the more rote things. So, for coaching, it’s certainly not having a computer provide a coaching session to an agent. It’s presenting insights to the coach that they may not have seen on their own so they can provide a better coaching session. As a result of that, it’s nudging. It’s creating this nudge that puts the relationship between the agent and the supervisor in a better context so there’s more camaraderie and lower agent turnover.
David Wasserman (17:41):
Nudging, in many cases, is putting people back on the course they already wanted to be on — they just need guidance to get there.
David Wasserman (19:45):
If you have a speech and text analytics product, the first thing you’ll want to do is listen. What are people saying and what are the results? What is the “do this, get that.” Start to accumulate the big buckets of what those things are.
If actions don’t align with your business goals or with customers want, then you can dig deeper and to start to understand, “Well, why is that happening? What’s going on in the process?” And then you introduce the nudging to guide people to do what they naturally want to do — certainly, what the customers want them to do to have a better result.