Vice President, Customer Experience Solutions
Since the dawn of the CX movement in the early 2000s, utilities have been riding the wave of customer-centered innovation. It’s safe to say that, by and large, how utilities interact with their customers today is virtually unrecognizable from what ‘run of the mill’ customer interactions looked like just a decade ago. Everything from the digital channels we now use to manage our CX programs to the range of process changes we’ve made to simplify key interactions (those proverbial ‘moments that matter’) have undergone substantive improvement, if not wholesale transformation.
Within the last decade, however, many utilities moved into a new phase of that transformation journey—finding new and creative ways to embed customer data into customer interactions and spawning a new generation of CX innovation. An increase in overall analytics capabilities, combined with new data streams enabled by utility smart meter deployments and IoT innovations, would initiate a level of innovation that we could only imagine a few decades ago.
Today, those innovations have converged with breakthrough advancements in Machine Learning (ML), Natural Language Processing (NLP), and Artificial Intelligence (AI) to help utilities design customer experiences that would make the Ubers and Amazons of the world take note.Think that’s overstating things a little? Perhaps. But there are now far more than a few utilities that have shown us what that level of CX innovation could really look like.
Here are five ways these utility "pacesetters," along with their ecosystems of technology partners, have used these latest advances in technology to reset the standard for utility CX:
Let’s start with the basics, the ‘table stakes’ if you will, for creating a better customer experience—the utility bill itself. Admittedly, most utilities have to some degree redesigned the presentment of that necessary but unpleasant part of the customer experience. For example, smart meter deployments have enabled most utilities to replace those sleepy year-over-year and month-over-month usage comparisons with more time-of-day, interval-based profiles of usage history. That’s a good start, although some might suggest that this is just the virtual equivalent of ‘watching your meter spin.’ I, for one, agree. That’s where advances in ML and AI come into play. Non-intrusive load monitoring (NILM) algorithms enable many utilities to detect the activation and deactivation of key appliances—from HVAC systems to water heaters and even electric vehicles—using just the interval-based load signature of customers and in turn, that gives customers an added level of visibility into what’s actually driving their consumption, and by extension, more control over their energy usage behaviors, ultimately leading to lower bills. But again, that’s just the starting point for opening up what has become a seemingly infinite set of CX possibilities.
Some might refer to this as personalization, but I prefer the term ‘adaptive.’ “Personalizing” can mean a lot of different things, from persona-based experiences built on traditional demographic and psychographic segmentation to development of seemingly customized offers based on broad usage profiles and clustering. Again, that’s not a bad thing, but what AI brings to the table is the ability to turbo-charge that personalization and render what is truly a customer ‘segment of ONE.’
Take, for example, algorithms that allow utilities to see the activation of an electric vehicle during a suboptimal time-of-use rate period and enable the utility to notify a customer of that event to can make a more informed decision. Or even better, to detect that an air conditioner’s load signature is deviating from its normal pattern, suggesting a potential malfunction and alerting a customer automatically to that condition. That’s a customer experience that truly adapts to what’s happening inside that specific customer’s home— personalization on steroids.
This is where it really gets interesting. Applying these advanced forms of load disaggregation and anomaly detection, many more advanced solutions have developed predictive intelligence around how the customer will consume energy in future. Take simple customer bill projections, for example. What utilities might think of today as a simple bill projection based on historical usage patterns quickly transforms itself into a truly dynamic forecast that takes into account a myriad of constantly changing variables. These variables could be real-time changes in weather forecasts or micro changes in behind-the-meter activity. Whether these are changes in customer’s solar production or EV charging behaviors or more fundamental changes in the lifestyle, the type we saw during the pandemic from increased work-at-home levels. Similarly, those same capabilities can be applied to the observed deviation in appliance-level load signatures mentioned earlier, thus enabling predictions of when an appliance might actually fail, and in turn, allowing the utility to extend a wider array of service offerings to customers.
And that predictive intelligence doesn’t just benefit the customer but can extend much more broadly across the utilities’ operations and even into systems and market operations activities. Think about the impact this could have to inform the design of network topology, the management of demand response programs, and even the forecasts relied upon by utilities and market operators to ensure the reliability of supply. (Folks in Texas might identify with this one a little bit!)
I had a colleague who held strongly to the view that utility customers don’t want to be engaged with. Having spent the better part of my career in CX, that sounded on the surface like heresy! But I must admit, I’ve become a bit of a convert.
Let’s face it; there will always be customers who prefer our legacy forms of customer engagement. Still, as trends have shown, more and more (particularly post-COVID) have migrated to our expanded ecosystem of digital channels—web portals, apps, push notifications, social media, the list goes on. The wider this ecosystem becomes, the more potential there is for noise and clutter. And that’s where things like advanced analytics and AI come back into play.
Ideally, CX should be far less about engaging more and much more about engaging at the RIGHT TIME, RIGHT PLACE, and RIGHT CONTEXT for a specific customer. Advanced technology platforms for CX orchestration are allowing utilities to combine behavioral insights referenced earlier with real-time situational intelligence on the customer to enable a truly seamless, frictionless and noise-free interaction. And sometimes, that means the utility is out of sight, out of mind, and available only when and if the customer wants deeper engagement.
Smart meters, smart grids, smart homes, smart cities (cringe/yawn) . . . it seems everything in the new energy space has become smarter. But if you look at where we are today, the ecosystem’s relative ‘smartness’ still leaves a lot to be desired. In the beginning, I’ll admit it was pretty cool to command my lights to go on and off, and watch that evolved into automated ‘routines’ that literally ‘start my office up’ at 7:30 every morning. And, of course, getting ‘Alexa’ to tell me the status of my electric bill (yes, that’s all my utility has enabled so far!) is a ‘nice to have.’ But none of this is really all that smart.
But fast forward to a world where all of the above is combined to create a truly intelligent experience, one that adapts to situational data and automates what it knows I need (and want), and we’ll start to see the real impact of these ‘smart’ promises. Fortunately, that’s not too far off. AI-powered CX platforms are fully capable of doing much of that today, and thier applications are only limited by the imagination. Combine the EV intelligence and notifications mentioned earlier with utility-sponsored ‘managed charging programs.’ Or a predicted supply constraint automatically adjusting thermostats based on preconfigured user preferences and limits. Not only are those things possible, but they have been brought to life by leading utilities already, with many more examples like these to follow.
For us, utility futurists in the crowd, many of the examples described here have been rattling around in our minds for some time. And it’s certainly been fun to watch these innovations move from the periphery of the CX landscape into the mainstream as leading utilities continue to transform themselves.
Thanks to the practical AI applications and use cases like these and how advanced CX platforms are bringing them into the mainstream, all of these innovations are now within reach for any utility looking to move into the next generation of customer innovation.
About the author:
Bob Champagne is Vice President, Customer Experience Solutions at Smart Energy Water, the leading AI powered Customer Experience and Workforce Mobility platform for electric, gas, and water utilities across the world. Bob is a 34-year veteran of the Energy and Utilities Sector, focused on driving customer-centric transformation across the utility value chain.