Eyewitness to history: Watching as the cloud transforms customer experience
A contact center solution and a contact center career, on parallel trajectories
Today, customer experience (CX) is the fate of the business. In a more virtual world where customers and sellers interact less often in person, the contact center is the CX. The cloud has driven a dual paradigm shift, elevating not only what customers expect, but also the ways contact centers are able to satisfy them.
This is more than a matter of degree. Using the cloud to manage customer contacts doesn’t just mean doing what you used to do, only better. The cloud introduces a new kind of responsiveness that wasn’t possible before. It has transformed the contact center from a cost of doing business, or at best a cost-neutral function, to a net positive that drives greater value from happier customers.
As a CX veteran, I’ve had a front-row seat to watch today’s cloud-driven contact centers come of age. I’ve watched predictive and responsive capabilities emerge and grow powerful—and I know they’re still growing. From that perspective, it’s inspiring to see what’s possible today and what’s on the way tomorrow. I joined Amazon when AWS’s easy-to-use omnichannel cloud contact center with built-in artificial intelligence (AI) and machine learning (ML), Amazon Connect, was still in beta. I remember that during my interview, they couldn’t even detail what it was all about! So, Amazon Connect and I have grown up together.
From months to minutes—and across the years
I started in the contact center field more than 25 years ago, when the cloud didn’t exist and the internet was just starting to take shape. The challenges then were hardware-centric—servers and connections and Private Branch Exchanges (PBXs). It didn’t take long for contact center operations to become software-centric instead. But even then, each system remained a walled garden, whether it belonged to a brand or to a contracted service provider. Each operation had to reinvent the wheel. More importantly, change was cumbersome, and not just in a technical sense. Even after software became prevalent, changing a feature or a setup meant working through multiple levels of approval and writing new code. Anything resembling agility came at a high cost. Often it didn’t come at all.
It amazes me today to look back on my first big contact center project. It was for a catalog clothing company in the mid-1990s. Our big achievement then was to set up networked automated call distribution (ACD). Did that mean customer contacts were automated? Hardly. It just meant the company’s two geographically separate centers could talk to each other and switch calls from one to the other, and it took us months to set it up.
Today, the challenges customer-facing organizations experience aren’t that different. After all, these challenges arise from the same sources: people who want information, service, and responsiveness. What’s different is speed, personalization, and flexibility. If that clothing company were to come to me today, I could get them up and running with an easy-to-use, omnichannel contact center in an hour. I’d be able put once-unimaginable power in their hands—to shape their CX instantly based on what was actually happening from moment to moment.
How the cloud puts you in the CX driver’s seat
The biggest power you get by moving to the cloud is control. Using a solution like Amazon Connect not only gives you a lot of feature and solution options—it also lets you manage and change them yourself, instantly, with a few clicks. You become the captain of your own ship.
The cloud also gives contact center operations a much greater command of customer data. It used to be a big task just to gather that information, much less quantify, visualize, and use it. To identify trends or sentiments, you had to transcribe recordings, then sic an army of analysts on the transcripts. Or you could extrapolate from samples of, say, 10 percent of your calls. That would give you faster results, but less reliable ones.
Now, a cloud-based contact center gives its users virtually unlimited access to data, and AI/ML tools can perform analyses based on huge datasets almost instantly.
What does that mean in practice for a contact center operator? Imagine analyzing the content of conversations in real-time, including the customer’s sentiment and trouble spots, so the agent can be more responsive and the business can adjust if needed. Imagine AI-driven natural language models that not only allow a contact center system to “converse” without taking a live agent’s time, but also to remember authentication details and other information so the customer doesn’t have to repeat them. When contact centers rely on the cloud, they can even detect what information an agent may need—in the moment, while the call is happening—and put it on the screen to save search time and avoid putting people on hold. The reality is that AWS can do all of that and more, right now.
From zero to a new center in hours—virtual or otherwise
Using traditional technology, it may take weeks at best to stand up a new contact center in a physical space with agents under one roof. Now we can do it in hours, and if necessary, the entire operation can be virtual—meaning agents can do their work remotely.
One big test of that evolution was the onset of the COVID-19 pandemic. They say 24-hour cable news came of age in 1991 during the first Gulf War. In much the same way, I feel cloud-based contact centers came of age in the spring of 2020. When people needed to start working from home, hardware-based contact centers weren’t able to shift operations to accommodate that need. Many organizations needed new contact centers where there were none before, to handle needs like health care, government benefits, and all the ecommerce that replaced shopping in shuttered stores. At AWS, we helped customers stand up new contact centers in hours, including ones for mission-critical COVID response hotlines around the world.
We haven’t slowed down since. Today, people throw around “AI/ML” so much that the term can seem drained of meaning. Now we’re putting that capability to use in ways I find spectacular. Think about a customer who wants to track a shipment. We already know a brand should strive to keep its customer experience consistent from channel to channel, so someone who ordered shoes from a desktop computer can check their arrival time using a cell phone, for example. Now the contact center can answer that call having already identified the consumer and predicted his or her concern—so the call might begin, “Hello, Mr. Jackson. Are you calling about your shoe order? They’ll arrive tomorrow.”
In the same way, past interactions can inform new contacts in a way that saves everyone time. If Ms. Santos browsed a selection of golf clubs a few days ago, without buying them or even putting any in a shopping cart or wish list, a cloud and AI-enabled contact center can answer a new call (or push out a notification) by asking, “Any chance you’re still interested in that sand wedge?”
A customer experience revolution everyone can join
What I find really satisfying about the advances cloud-based contact center technology makes possible is that they’re so broadly available. Much of what we offer today was theoretically possible before—if your company and budget were big enough. The cloud democratizes progress because any size company can enjoy these features and advantages on an appropriate scale. Today a 10-agent contact center can implement the same resources as a 10,000-agent center, at the same cost per interaction. Because it’s so easy to adjust, it isn’t only the big players who can afford to risk new things. Everyone enjoys the ability to experiment without fear of failure, which is where innovation comes from.
I talked about growing past the fear of failure. To me, that’s the story of Amazon Connect and my time here. We’re never afraid to experiment, and our culture will always have the spirit of a startup in its DNA. Am I an old dog learning new tricks? Constantly. Guilty as charged, and I’m loving it.
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Mike Wallace is a Senior Manager of Solutions Architecture for Productivity Applications, including Amazon Connect.