It’s no secret that technology is advancing—and fast. Not only has a growing percentage of the population become surprisingly tech savvy, but we’re seeing rampant growth in AI (artificial intelligence) and similar innovations, giving marketing and customer experience leaders in our industry a lot to keep up with. Can you even imagine a world where you weren’t constantly racing to keep up with technology? What if your technology could keep up with itself and improve over time?

In fact, such technology does exist. It is referred to as “machine learning,” which describes certain types of programming that allow computers to change and improve in response to new information. And while machine learning may seem like futuristic voodoo, you’ve likely encountered it before unknowingly.

Spam Filters

A great example is the concept of a spam filter. Spam blockers have gotten substantially more robust over time as they’ve learned to dissect the anatomy of a spam email. Filters cross check senders against blacklists of known spammers, scan for whether an email was sent to multiple recipients, and most notably: learn to flag keywords related to Nigerian princes, little blue pills, and money-back guarantees.

What’s so powerful about machine learning is that, as more and more users flag emails as spam, the algorithms that detect spam constantly grow smarter based on the new information. In other words, spam robots continue getting better at their jobs—challenging spammers to be a lot sneakier with their wording to get through the filters.

That said, machine learning has made your inbox a safer and more hospitable place to be.

Facial Recognition

Facebook users are highly familiar with the next example of machine learning: facial recognition software. While just a few years ago, users had to manually tag friends in photos, Facebook’s algorithms have gotten so powerful that they can identify who’s in a photo and suggest tagging with astounding accuracy.

Just as we’ve seen with spam filters, facial recognition gets progressively smarter. As users tag their friends’ faces, the facial recognition algorithm develops an understanding of which parts of photos contain human faces, it notes specific traits of different humans, and finally, it has the ability to recommend a person to tag.

Implications for Customer Communications

The utility industry will benefit greatly from machine learning developments, presenting opportunities to positively transform the customer experience. From apps for utility customers to keep track of their home or building’s energy consumption to programs that help utilities identify the next best offer or action to recommend to customers, there are many solutions on the market to help utility customers glean more savings (and more satisfaction with their utilities).

At Fiveworx, we use a machine learning platform to identify your customers’ product and service propensities and communication preferences, communicate with them accordingly, learn from their ongoing engagement with the information they receive, and continuously improve their stream of information over time, all while making each insight available to you for further success. As our engine learns what information to send your customers, when to send it, and in what form, you see the dual benefit of improved customer experience and greater uptake in utility programs, products, and services.

That’s the type of magic made possible by technology and machine learning, and it’s the focus of our work here at Fiveworx. Our robust communication tool will only grow more useful over time—a technology that truly keeps up with itself.