S4 Ep. 9 Generative AI, employee experience tech and CX evolution

Ginger Conlon (01:43): 

It’s no surprise that AI was the hottest topic at Enterprise Connect. But what about AI is getting all the buzz? Let’s dive into that. One area that kept coming up is that if you want to get the most out of AI, you need to start — if you haven’t already — moving your CX platform to the cloud.  

Michael Logan (02:11): 

I look at it this way. We had this CX evolution of moving from premise-based solutions to cloud solutions and that transition happened pretty rapidly for technology. Now we’re ready to implement AI. And the first step of implementation is directly related to being on a cloud platform. You can take advantage of robust features and an infinitely scalable solution, as well as new features that come rapidly as opposed to waiting for the quarterly update for your software solution. It truly is step one to getting to an automated and augmented solution.  

Ginger Conlon (02:57): 

During the show, you spoke to Natalie Dechellis, a senior director and product marketer here at Genesys. She said that a cloud solution allows you to have that push-pull model to share data across your entire CX stack, which is critical today when we’re talking about AI. You better have access to data, especially, as much as you can, in real time and high quality.  

Michael Logan (03:23): 

Absolutely. There’s no better way to do that than having APIs working in the background. It used to take so much development to get into a system of record and it took constant updates. Every time your software solution or something tied to it upgraded, you had to rewrite it in some instances or go and repair it or fix it. Those days are gone. Now that data feed is continuous, it’s constantly up to date and that allows you to take advantage of things like having that ability to surface relevant data for agents to respond to customer inquiries in real time. 

Ginger Conlon (04:06): 

During the locknote session that wrapped up the conference earlier today, David Michael said, lead analyst at TalkingPoints said, “AI is a magic trick, but we’re not all magicians.” And he added that AI needs data. Many organizations don’t have or don’t feel they have the data/data quality that’s needed. And he also said that the magical experience we want from AI is personalization, but it’s going to take time to get to where we need the data to be to do that optimally.  

Michael Logan (04:46): 

I asked this question a few times during our sessions and during our interviews: “What does it take to get someone started?” And in my opinion, what I’ve seen is really having the data that your CX solution provides can get you started and at least get you on the path to a stronger AI experience when you can automate enough to get a reduction in handle time or after-call work. Those are a clear return on investment in that strategy.  

Ginger Conlon (05:31): 

Another AI related topic that was pretty hot — no surprise — was generative AI. During one of the sessions, David Myron, a principal analyst at Omdia, said that the top five generative AI technologies that contact centers plan to deploy over the next 12 to 18 months are document creation for knowledge basis, text chat response, agent assist, post call notes/summarization, and email responses. This is from recent research they’ve conducted.  

Michael Logan (06:08): 

Going back to what we talked about on cost savings, the ROI there, as you reduce average handle time, you reduce the burden of repeating yourself a million times with often-asked questions. The email response one did surprise me, but again, that’s not a surprise, right? It’s the email channel is something we don’t think about as much as we used, but it’s great to know that it’s a big part of generative.  

And for those that still look at generative AI and say, what is it? It’s that ability to take a vast amount of knowledge and create conversation with very little prompt; ask a question, it’ll respond. The reason CX is moving a little slower on that front — because the technology has been there for a while — is because we want to make sure that information is correct.  

The biggest surprise that I’ve seen with generative AI is around when we do the summarization, the amount of time we’re saving on after-call work is a bigger number than we anticipated. And even average handle time is reduced because agents aren’t trying to keep up with typing.  

Ginger Conlon (07:22): 

Natalie Dechellis said that one of our customers has saved two to five minutes on average per call because of auto-summarization and then having that agent human in the loop to just do the review versus having to do an entire summary.  

And Robin Gareiss, CEO and principal analyst at Metrigy, during her session echoed what David Myron was saying, that generative AI is incredibly valuable for productivity-related activities. So, those summarizations, composing emails or chats, content creation for self-service generating articles and content for agents to use during interactions — we’re just scratching the surface of what’s going to be possible  

Michael Logan (08:13): 

And something that’s overlooked in that conversation: Remember that AI is here to be an assistant. It’s here to augment what we do and assist us with what we do. And when we talk about summarizing an interaction, typically that was done from scratch. Agents had to write out everything that occurred during a call. The summarization, at least at the bare minimum gets you started. AI is not 100% the response, it is a piece of what the final response is. Now the agent just has to add the bits that were not picked up.  

I like to highlight that because we talk about AI so much, we forget that it’s not a replacement of the agent, it’s an assistant to the agent. And if you can get halfway there with the notes and halfway there with a highlighted response or an after-call work, you are going to reduce time and reduce that stress on the agent. Turnover is still happening. But making this job more enjoyable, easier to navigate these complex customer inquiries… anything we do to help is an advantage.  

Ginger Conlon (09:32): 

Absolutely. Robin Gareiss of Metrigy said that 26% of the CX leaders they recently surveyed for one of their reports are using AI to reduce employee attrition. So, it’s not just about productivity, which is so important, but it’s also about that agent experience. 

Ginger Conlon (11:33): 

Going back to Robin Gareiss of Metrigy, she has research that shows that when agent attrition is below 15%, customer satisfaction improves by 26%. And David Myron from Omdia said they’ve done recent research showing which types of AI businesses plan to deploy over the next 12 to 18 months, specifically within the contact center and for customer experience. He said the top five are digital customer contacts, analytics, digital customer contact, analytics; customer journey analytics; sentiment analysis; intelligent knowledge base; and intelligent call routing. All of these are ways to support the agent around the actual interactions.  

Michael Logan (12:37): 

There are two on there that I want to speak to because I don’t think they get enough press. One that stands out for me is the analytics around the journey. When you can as an organization start to parse out what’s happening along that customer journey; not just a single interaction, we’re talking about all interactions that have that same route. We can look at them all and see where there’s breakdown, where there’s bottlenecks and improve upon them and continue to improve upon them. It’s not a one-time analysis, it’s a continuous analysis. So, if something breaks along the way, to be able to react in real time.  

And the other one that I wanted to highlight is the ability to predict using predictive routing. What is the best resource for that single interaction at this given time? Again, it takes data to understand your agent, and it takes data to understand that customer, to drive that predictive routing scenario.  

When you route the interaction to the right individual, you’re going to get a better outcome. You’re going to get a happier customer. You’ll get a savings in handle time because it’s the right person with the right interaction.  

Ginger Conlon (14:32): 

Benefits like you just mentioned were hotly discussed during many of the sessions around using AI for the employee experience. Reduced handle time came up as one big benefit, time saved due to auto-summarization like we discussed.  

Brett Weigel, general manager of digital AI and Journey Analytics here at Genesys, said creating a “single pane of glass” is another way to use AI to deliver business value. And that’s basically when you have that unified desktop where agents have everything they need at their fingertips and information is also coming to them through those AI-powered agent assist tools that increases productivity and, like you pointed out earlier, lower stress because now you’ve simplified both the interface and the interactions.  

Michael Logan (15:29): 

It goes beyond just simplifying the interface for the frontline agent. It also helps the supervisor. Think about what we had to do just a few years ago. For a supervisor to get a certain insight into a recording, they’d have to open their recording solution and log into it. And then to look at the QA response, they’d have to open another solution. So, think about the time saved there, where now we have AI listening to every interaction to do some of the legwork.  

[With AI and cloud we’re] driving a truly revolutionary CX experience, and we’re doing it from a single interface.  

You’re able to not only create your bot, upload your knowledge, and then tie a bot to that knowledge and create the agent interface that is prompted in front of the agent as they take those interactions, but you’re doing it from one screen. And that alone is a huge benefit because when we talk about AI, one of the top things we talk about is you need data. If all your data lives in one solution and you’re able to orchestrate this experience from one place, and your cloud solution and all that AI is tied to that same data, natively to that solution, you’re really streamlining so much. I think there’ll be a point where we think, why do I have to log into something else to do anything else?  

Ginger Conlon (17:27): 

All the things that we talked about relates to the theme of Enterprise Connect overall, which is keeping momentum on CX transformation moving forward. If you think about using AI throughout more of the customer and employee journey, and then using AI to support the employee experience more, and improving productivity and lowering attrition and lowering stress, those are all essential elements of keeping your CX transformation moving forward.  

And then, as a big part of that transformation, the contact center becomes a center of excellence for the organization that advocates for the customer — because data is coming into the contact center from other connected channels and functions and going back out from the contact center to those other connected channels and functions, so we’re creating a more seamless, cohesive end-to-end customer journey for the customers and the agents. We’re orchestrating those more personalized, empathetic experiences.  

Michael Logan (18:50): 

There’s so much interesting innovation still to come. We have to start to implement the things that are available to us now, so that when those innovations come along, they’re easily adopted. And we get into this mindset of there are always improvements. That’s why we talk about journey analytics. 

There’s never an end to innovation. There’s always the next transformation. We talk about what’s happening in five years from now, what’s happening in 10 years from now, and it’s all driven around these easy-to-use tools that we’re providing.  

Ginger Conlon (20:02): 

Absolutely. And I love your point about the ongoing journey. There’s the day-to-day, customer journey and employee journey, but then there’s also the ongoing CX transformation journey. I like to liken it to professional athlete — and it’s baseball season, so I’m just going to have to compare it to a baseball player. Imagine you have a baseball player who is a star hitter who’s making $20 million a year, and you ask him at the beginning of the season, “What are you working on?”  

“Oh,” he says, “I’m tweaking my stance so I can be a better hitter.” Even someone who is at the pinnacle of their career is still looking for ways to improve.  

No matter how amazing your customer experience is and your employee experience is, there are ways to make it better. There are new technologies coming on board to make it more of a win, not only for your customers and employees, but also for your business. So, I love that Enterprise Connect has the key theme of keeping the momentum on CX transformation moving forward, because that’s what CX is all about.