Fresh Angles on AI, Data and Personalization in CX

The theme of Enterprise Connect 2024 centered around maintaining momentum in customer experience (CX) transformation. And attendees were eager to get all the information they could about strategies and new technologies available to wow their customers and help their agents succeed.

Two topics stood out as change makers for the industry. Harnessing artificial intelligence (AI) was the No. 1 recommendation for improving CX and EX now – and in the foreseeable future.

Data, specifically how to properly use the mountains of valuable customer data organizations have, was another major topic. AI loses its impact without robust, quality data.

Experts at the show stressed the importance of getting more actionable insights from customer data to give them the personalization they crave. And equipping frontline agents with the tools necessary to access that data empowers them to resolve customer issues faster. It not only improves customer engagement, but it also alleviates their on-the-job frustrations.

Here’s what industry analysts, consultants and Genesys experts had to say about AI, data and top technologies to include in your customer experience strategy to gain that competitive advantage.

What’s one way AI delivers business benefits in customer and employee experience?

“One area is the agent experience and using solutions like agent assist to help answer tough questions in real time. This means you don’t have friction within the customer experience during an engagement. It improves quality management and performance evaluations. Also, using generative AI to handle interaction summarizations allows agents to get more done.

We’ve seen quantifiable impact there. One early adopter of auto-summarization is saving about five minutes of after-call work per agent. When you think about five minutes across all your agents, that’s significant. That means you’re getting customers through the queue faster and interactions get a little bit faster. And you can handle more capacity with your current staff.”

– Nathalie DeChellis, Senior Director, Product Marketing, Genesys

“AI is important as we think about modifying conversations from being more transactional to being more interactive. We’ve seen it already in having conversation summaries — enabling agents to focus on those one-on-one customer conversations rather than having to focus on documenting those conversations. Letting the technology do the summarization improves both the customer and employee experience.”

– Josh Goldlust, VP, Product, Genesys

“We can understand what’s happening within conversations. And using that, we can get sentiment analysis, empathy analysis, topic spotting. And we can use that to understand employee behaviors, customer behaviors and the customer experience. And that’s just the starting point for AI today.

On top of that, there’s agent-assist capabilities — and that’s something organizations can deploy today to help agents be more efficient in their jobs. They can use that to answer knowledge quicker, to get summarizations at the end of their call. Right from there, you can gain performance efficiencies and improve customer and employee experiences.”

– Rakesh Taylor, VP of Product Management, WEM, Genesys

What’s one AI misconception that’s stalling progress? And how can CX leaders overcome that?

“One misconception that CX leaders have about AI is that it’s a one-and-done thing. They think they can just deploy AI and they’re done with it. But the truth is: It needs constant refining, constant tuning and training, constant updating. You have to look at your knowledge bases, your data sources and continuously update them with quality data.”

– Blair Pleasant, President and Principal Analyst, COMMfusion LLC

“AI is just two simple letters, but it seems so complex. So, I’d say one of the biggest misconceptions is that you have to have it perfected before you launch.

There’s a lot of value companies can get right away from taking simple steps, whether it’s using AI for self-service or for a knowledge portal or being able to expose knowledge automatically to your agents. There are a lot of places you can start small. Start to gain the benefits and then start evolving some of your processes. It doesn’t have to be an all or nothing.”

– Josh Goldlust, VP, Product, Genesys

“When companies think about getting started with AI, they often perceive that it’s really hard to get going and that it’s hard to assemble a team that has the necessary expertise.

The reality is you can get started with pieces. Genesys offers convenient ways to get started with your conversation and behavioral data that already exists in the system based on using our products. And with that, you have a starting point that’s easy to adopt and to use — and business users can do it, too.”

– Brett Weigl, GM, Digital, AI and Journey Analytics, Genesys

What’s one piece of advice you’d give CX leaders on getting more value from customer data?

“CX leaders have to look at integrating their data — more than just their contact center data. They need to look at their CRM data, for example, and put it together with data from other channels and functions and look at the full story. The integrated data shows the end-to-end customer journey.

Although some organizations are already doing that, others haven’t made that connection yet. But today, it’s necessary to look at all the data, not just contact center data.”

– Robert Lee Harris, President and Principal Consultant, Communications Advantage Inc.

“CX leaders can get more value from their customer data by actually using the data.

Organizations collect so much information. They have it from so many different sources. They need to integrate all that data into one source, and then use the data. It can tell you about trends; it can tell you about patterns you can take action on.

So don’t let the data go to waste. Integrate it. Take advantage of it. Find ways to solve customer problems using the data you have.”

– Blair Pleasant, President and Principal Analyst, COMMfusion LLC

“CX leaders need to be looking at not just the digital side of the customer experience, but also the voice side — and the data that goes into it.

If they don’t have all that data, they’re not going to measure their contact center correctly. They need it to manage their SLAs, to deliver a better customer experience, to manage workflows — especially if they’re looking into a workforce engagement management [WEM] suite to provide interaction analytics.

Organizations today should be using text and speech analytics from WEM as a frame for collecting even more data to increase and continually optimize their knowledge base.”

– Steve Leaden, President, Leaden Associates

“Staff for it. Organizations need to hire people and have them do the job of using customer insights to provide more value to the organization — to extract meaningful information from the data they’re getting — and not have it be part of someone else’s job.”

– Melissa Swartz, Founder, Swartz Consulting, LLC

“One way CX leaders can get more information from their customer data is to learn by being their own customer. Go through a full customer journey, follow what the customer experience is like, see where the pain points are, see what you would want to change if you were your own customer.

When you go through the whole process — start to finish — of what your customers experience, you can then use that qualitative data with other insights to improve that experience.”

– Kyle Leaden, Consultant, Leaden Associates

“Think about that push and pull of data. You want to make sure that you’re getting data from your critical CRMs, ERPs… all those places. And within your system, you’re generating a lot of data that could push back into the machine learning models so they have something to aggregate, something to analyze.

When you think about the role of generative AI, it’s creating something out of something. If you have nothing for it to create from, you’re at zero. You need to make sure you’re pumping enough data into your CX system and that you’re generating enough data across voice, digital, bot interactions, WEM, etc.

And you need to analyze it properly across positive and negative sentiment. You need to make sure your AI models are running enough data to give you an output that’s optimized and that’s beneficial for your business.”

– Nathalie DeChellis, Senior Director, Product Marketing, Genesys