Over the past 15 years, I’ve seen the course of customer experience intelligence shift drastically, and my home state become a hub for the industry.
While I wholeheartedly believe Utah—home to InMoment’s global headquarters—is the most inviting and majestic locale in the entire United States, the climate and geography are certainly not for the faint of heart. Icy cold and snowy winters are followed by long, dry summers, while the shoulder seasons—spring and fall—last about as long as a head cold (but let me tell you, those few days are absolutely glorious). Yes, we have the Greatest Snow on Earth, the Wasatch Range, Uinta Mountains, and five nationals parks…and we also have rattlesnakes, flash floods, and the occasional inversion (a layer of cold, pollutant-filled air that gets trapped in the valley between winter storms).
But none of that compares to the terrors of living in Florida.
I say this partially in jest (see: alligators, cockroaches, mosquitos, and an average daily humidity flirting with 100 percent), while recognizing the harsh, potentially life-threatening realities of living in a tropical climate. We witnessed this truth earlier in the year with the devastation of Hurricane Irma.
In June, two InMoment employees relocated to the gulf coast of the Sunshine State—one accepted a CX leadership position with Foot Locker, while the other was afforded the opportunity to live closer to family while remaining a full-time (remote) employee at InMoment. Naturally, InMoment headquarters was concerned about the well-being of these two newly-minted Floridians and their families as Irma came barreling toward the state in mid-September.
Anyone who tracked this massive storm is familiar with the Cone of Uncertainty. This theory, which describes the evolution of certainty throughout a project or event, is used by meteorologists to provide guidance to local governments, officials, and residents as storms approach. When a tropical storm first becomes a hurricane, the Cone of Uncertainty is, well, quite uncertain. It’s narrow at one end (we have a good idea where the storm will be in an hour), but wide at the other. The further out we try to predict, the larger the margin of error. It’s scientific—but it’s also a bit of a guessing game.
Taking drastic action based on so little certainty would be unreasonable, impractical, and irresponsible. Imagine if we could only see the forecasted hurricane track once, and many days out. Would we evacuate the entire Eastern Seaboard each time a storm popped up in the Atlantic? We might if we had no other choice. Luckily, the forecast track is updated every few hours, and while we may not know the storm’s exact path until it actually makes landfall, the closer it gets, the more certain we become.
In the past, I’ve used the analogy of a car’s dashboard to refer to customer feedback data: the speedometer tells you how fast you’re going (i.e., metrics such as OSAT and NPS) but it’s the GPS (i.e., analysis of unstructured, qualitative data) that ensure you successfully navigate to your destination. While this analogy still rings true, I’ve started to think about CX strategy in terms of the Cone of Uncertainty, and how advanced models and an even deeper understanding of customer stories can reduce the amount of guessing required.
All companies, whether or not they’ve implemented Voice of Customer programs, have a broad view of the customer journey, a general sense of customer expectations, and likely some idea of how to improve customer experiences. This is the wide end of the cone (i.e., evacuating the entire east coast from Miami to Boston). In other words, it’s not very helpful. If you manage a CX program and all you can see is the wide end of the cone, it’s probably time to update your resume on Linkedin.
As I mentioned, when forecasting a hurricane’s track, we typically don’t know what the storm is going to do until it’s actually doing it. Due to wind, water temperature, and other variables, at only 12 hours out, the average forecast track error is still nearly 10 miles. That could mean the difference between a direct hit and a relatively minor meteorological event! Unlike a hurricane, predicting how to improve customer experiences is actually quite an accurate science—assuming you have the right model in place. We’ve been feeding our CX machines, algorithms, and engines with customer feedback data for nearly 15 years; the more data we put in, the better they’re able to prescribe and predict the path to better customer experiences with pinpoint accuracy.
Going back to my dashboard analogy, from InMoment’s inception, CX technology has progressed from a basic speedometer to an advanced GPS, but what’s next? From our standpoint, it’s automation. It’s a self-driving CX engine—based on more than the analysis of structured data and predefined KPIs. As algorithms, machines, models, and data improve, the Cone of Uncertainty will become less of a cone and more of a line—a direct path from Point A to Point B. Companies will no longer rely on tools, but rather always-on CX guidance. An analyst inside the platform—reading tens of thousands of customer stories each week—that understands expectations and experiences, and targets recommendations to various personas within an organization.
Customer experience initiatives should not be a shot in the dark—trial and error. With real-time updates, alerting, and recommendations—fueled by the always-on ingestion of customer feedback data—customer experience initiatives should not be educated guesses, but calculated certainties.