And as mobility has gone mainstream, the cloud has drifted into the business landscape, and the Internet of Things (IoT) has taken shape, the opportunities to interact on a more personal and relevant level also have grown.
Clearly, customer experience (CX) is now an anytime and anywhere proposition. This has businesses completely rethinking and re-evaluating the way they design their networks, build out IT infrastructure, and, ultimately, interact with customers. At the center of all of this now is a framework called edge computing, which moves computation, storage, and other tasks outside the network core and to the collection source, such as an IoT device. The end result: a faster and more satisfying CX because the compute process—and decision making—takes place where the data is generated.
“There’s a growing need to convert signals into action and act on data while it is fresh,” said Anjul Bhambhri, vice president of platform engineering at Adobe.
The objective should be to create a more natural experience using real-time data, artificial intelligence (AI), and automation, said Scott Likens, partner of emerging technologies at business and IT consulting firm PwC Likens. This requires organizations to revamp their business strategies and the technology platforms they use to reach customers. It means rearchitecting networks, devices, and applications to support an edge model.
“Customer interactions have moved beyond keyboards and mice,” Likens said. “We have entered a world where natural language interfaces, image recognition, gestures, and virtual immersion—including augmented and virtual reality—are redefining the rules of engagement.”
To be sure, organizations must evolve beyond a mindset that simply deploying more digital systems is better and relying on these systems to do new and intriguing things is enough to boost customer relationships. CX on the edge requires a deeper understanding of how to use data, analytics, and clouds outside the hub-and-spoke model of the datacenter. It also demands creative thinking and a thorough understanding of what makes customers tick, including how to reach them on their terms.
All of this, said Teresa Tung, managing director at business and IT consulting firm Accenture, requires “a smarter and more responsive edge framework.”
Sharpening the Edge
According to Adobe’s Bhambhri, edge computing rests on three primary pillars: moving compute closer to where the data originates, running decisioning services for experience optimization at the globally distributed spokes, and scoring machine learning models at the edge for the right next best action (predictive analytics). 5G will further accelerate this trend, she said.
All of this requires fast processing of high velocity data to gain deeper insights. The end goal, Bhambhri told CMO by Adobe, is to “make experiences as customer-centric as possible.”
A well-designed edge framework, PwC’s Likens said, allows “information to flow at many different levels—from the physical edge that consists of actual devices and hardware to the virtual edge with simulations, augmented reality, and virtual reality.” It succeeds by tapping computing power on various chips, devices, and software to collect, store, and process information more efficiently.
Innovation is at the center of effective edge computing frameworks. New technologies—and the combination of these digital systems—introduce opportunities that didn’t exist a few years ago. This includes a level of personalization, contextualization, and timeliness that can transform a brand and the way customers view it.
Bhambhri referred to this as “the right experience at the right time.” It’s driven by defining the “insights-to-action” process both qualitatively and quantitatively.
It’s essential to think beyond smartphones and apps and enter the realm of what Likens called “hyperconnected networks.” For example, a customer might prefer to order a pizza from a smart speaker at home or while driving. Some newer vehicles already come with in-car payment systems that allow motorists to order and pay using voice commands or touch controls. By pushing transactions closer to the point of interaction, an edge system can process the payment before they pull into a drive-through window, Bhambhri said.
“If you know the person orders a certain type of pizza, then you can offer the option to order it again at the push of a button or with a voice command,” Likens said.
Using a combination of clouds and local processing, the system optimizes and speeds processing. “You can provide notifications about when to pick it up and send a receipt and acknowledgment,” Bhambhri added. “The entire process can be seamless.”
Domino’s Pizza is among the restaurants that have already introduced such a system. Its Pie Pass allows customers to skip lines and receive other perks, including viewing a welcome board that speeds the handoff upon entering a store.
Airlines, too, are transforming CX through the edge. Some, such as Delta, American, and United, now offer real-time updates about flights, boarding, and baggage through integrated sensors and IT systems. Travelers can receive these notifications via a wearable device, such as an Apple Watch or a smartphone, and know precisely when it’s time to board or what carousel to head to for their baggage after landing—all without having to put a bag down and enter any data. In addition, apps make it possible to change seats, request upgrades, and order meals.
Organizations benefit by finding ways to expand and improve experiences, Accenture’s Tung said. For example, fans at a concert or sporting event might tap into feeds from several cameras and select a view—or instant replay—on their phones. They might view augmented reality over images.
“It’s possible to curate the content and deliver contextual advertising,” she said.
Different business outcomes, different algorithms, and different computation models don’t just happen. A business must define the North Star for their digital experience—and then leverage the technology to materialize the vision. This means evaluating current IT architectures, networks, cloud services, and platforms, Bhambhri said.
It also translates into new partnerships and a willingness to explore and experiment with new technology components, including analytics and AI systems that may incorporate machine learning and deep learning. Getting automation right is critical, experts agreed.
“You have to be able to do the computation and scoring of ML models on the edge,” Bhambhri noted. “It requires new and different types of hardware and software.”
This requires an understanding of application programming interfaces (APIs) and connection points that extend across companies and data—along with the software that drives many edge functions. In addition, the edge requires a more robust and multidimensional framework than packaged software can provide straight out of the package.
“You can’t just use natural language algorithms and facial recognition out of the box. You really have to test them and make sure they are valid and unbiased,” Tung explained.
Without adequate checks and balances, apps and advertising simply become more “noise” or drift into the creepy zone. And while it’s tempting to place trackers, beacons, and third-party data collection systems on devices, stepping over the line and creating the illusion of spying on customers can undermine trust.
“Data is everywhere—in the cloud, on devices, and on edge storage,” Adobe’s Bhambhri said. “You essentially multiply the number of places data exists exponentially. Data governance becomes a critical imperative for CXM.”
As a result, organizations must revamp data governance models and re-evaluate security and privacy settings, including how much control customers have over their own data. Regulations like the California Consumer Privacy Act (CCPA) add to the task. Ultimately, organizations should strive for a model based on trust rather than protecting a specific system, application, or data repository. This typically means better authentication, data encryption, and network visibility.
“The types of protections that are required on the edge are not typically built into networks and IT systems,” Likens said.
The end goal should be a business framework that promotes ongoing research and exploration of digital technologies, key partnerships, fast prototyping, experimentation, and scaling projects when and where it makes sense—and maximizes opportunities.
“It’s not just the collection of raw data that matters. It’s the enriching of data—coming from various touch points—that provides insights,” Bhambhri observed. “Instead of thinking about one edge to collect data, you have 5,000 or 10,000 globally distributed edges.”
“You really have to think about the edge space differently,” Likens said. “In many cases, a technology by itself is cool, but when you combine it with one or two others and build an edge framework to support them, you wind up with something that can change your business and perhaps the world.”