The past is never dead. It’s not even past yet.
That famous quote comes from William Faulkner and it’s often trotted out to provide meaning and important to various situations, speeches and commentary. Allow us at PYMNTS to do our own small part in that ongoing effort, and apply that quote to the world of B2B customer experience — and the never-ending push to build a better digital ecosystem around that concept.
Indeed, even as artificial intelligence (AI) and other of-the-moment technologies start to transform that space, it’s worthwhile to recall that such efforts were born in the early days of the Internet some 20 years ago, according to Rob Tarkoff, executive vice president and general manager of Oracle CX Cloud. He recently spoke with Karen Webster not only about the roots of modern B2B CX efforts, but discussed the moves taking place in that particular area of commerce and payments — moves that promise to reverberate into 2020 and beyond.
Back then, he recalled — during the days of Commerce One and Oracle working together in B2B supply chain and similar spaces — businesses were still more than a bit uncomfortable putting their data and operations onto the Internet. But the goal would likely seem familiar to pretty much every B2B professional in 2019: Create tighter ties between buyers and sellers, and construct a system that can not only provide personalized product and service recommendations, but even anticipate future customer needs and produce a response in a proactive, cost-effective manner.
“We didn’t have good Internet at the time,” Tarkoff said. But now, he said, the technology has evolved in such a way that makes for relatively easy understanding among B2B players about how to go about all this. And that is happening at a time during which the concept and practice of the digitally enabled customer experience takes on more focus and importance in both the B2B and B2C worlds. A robust, predictive and personal customer experience (CX), arguably, is becoming the name of the game.
“CX is definitely a massive change in consumption,” Tarkoff told Webster. “And as consumption changes, payments flows change, and the idea of what constitutes an asset changes.”
He provided one example — an example not on first glance related to payments or financial services, but which could indeed play a major role in those areas vital to the professional lives of PYMNTS readers. Consider a piece of gym equipment — or, really, any other item important to the operation of a particular business. All such gear depreciates over time, but thanks to sensors, the Internet of Things, cloud computing and even AI predictive capabilities, the supplier of such equipment can proactively make repairs and maintenance before things get too degraded. “It all happens before you even know you have a problem.”
That, in turn, can give financing providers more confidence in the business, and also serve to spark more sales of subscription services and products by that particular business, he said. “Financial services are getting this positive benefit from improved customer experience and improved customer relations,” Tarkoff said. “That leads to continued investment in companies.”
Data, of course, is the biggest driver in all these real and looming improvement in the customer experience, whether B2B or B2C. “Nothing is more important than a person’s past purchases,” Tarkoff said. What a company knows about you a consumer — not only what you have paid for, but how often you have bought it — helps its systems, including those powered by machine learning and AI, to make better predictions. And the better the predictions, the more sales at less cost can take place — helping to boost the bottom line.
Indeed, some two decades after those earlier, seemingly primitive efforts to make a more robust customer experience, today’s data technology — including machine learning and artificial intelligence — are able to tell (the all-important) difference between new digital visitors and returning customers. “You have the ability to tie first-party and third-party data together easily,” he told Webster, “and run machine learning against that ID graph. That can help you figure out what to come up with for the next big offer.”
What seems so fresh and news often really isn’t — or, at the least, is more anchored to the past that one might grasp upon first glance. Even so, all this new technology is doing heavy lifting when it comes to that eternal work of making a better customer experience.