How Artificial Intelligence & Machine Learning Could Shape the Future of Intelligent Billing


In recent years, artificial intelligence has emerged from the realm of science fiction and become a very real tool that, depending on who you talk to, will either leave humans jobless and purposeless or improve businesses operations in every industry by taking over mundane and data-heavy processes and leaving human employees with more time and energy to think and work creatively.

Here at goTransverse, we’re excited about the ways artificial intelligence and its partner, machine learning, could enhance the world of intelligent billing by improving the customer experience and giving our clients new sales opportunities. But before we dig into that, let’s step back and clarify exactly what we mean when we talk about artificial intelligence and machine learning.

Artificial Intelligence refers to the field of computer science that creates machines that are capable of solving problems more quickly and accurately than humans can. Traditionally, AI works by analyzing a set of inputs and coming up with the correct output more reliably than we can.

Machine Learning is a subset of artificial intelligence — just one specific approach — and it reverses the traditional AI development method. Rather than teaching the computer the required logic to solve a problem (feeding it inputs), machine learning gives the computer a set of known answers to the problem. Then the computer is responsible for generating, or learning, the logic it needs to solve similar problems.

To be very clear, we’re not talking about the almost-human type of AI that can solve any problem. That’s still confined to science fiction. We’re talking about “applied” artificial intelligence, which refers to AI designed to accomplish one particular task. This task could be searching Google based on voice commands, parallel parking against a crowded curb, targeting advertisements based on individual web users’ preferences or even composing relatively tolerable jazz.

Artificial intelligence is already all around us, and its capabilities are only going to expand and improve.

How Will Artificial Intelligence Enhance Intelligent Billing?

The key for businesses looking to identify opportunities to embrace AI is the data it can use to both train and apply algorithms. In a recent post, I explained the first question to ask is what data the organization has unique access to and what AI and ML could do with that data to set it apart from the competition.

 “An organization like JPMorgan Chase has access to billions of purchase records and knows your own unique credit card buying patterns and behavior. It makes perfect sense, then, that Chase has used AI-based algorithms that can almost instantaneously detect anomalous purchase behavior at the point-of-sale and notify its users of potential fraud, which increases its customers’ confidence and loyalty to is profitable credit card offerings. Netflix and Spotify have unique viewing and listening data that allows them to know exactly which movies and music you like, so it was a natural step for them to introduce AI to augment their customers’ processes of exploration and discovery with recommendations of new movies and music, respectively.”

– How to Start Thinking about Artificial Intelligence and Machine Learning for the Enterprise

Intelligent billing platforms like goTransverse have a particularly fascinating opportunity to support growth, because we have access to nearly limitless consumer usage data from our clients and their customers.

Automation (which is not the same as artificial intelligence) already allows us to manipulate that data more quickly and accurately than could ever be done by hand, enabling flexible, transparent, frictionless billing processes. But when we add artificial intelligence and machine learning into the mix, we’ll be able to do so much more. Here are just a few examples.

1. Recommend New Products and Services

An AI-powered billing system could detect usage patterns in existing products or services and make recommendations for new offerings based on inferred user preferences. For example, if users are consistently ignoring certain features of their subscription and adding on others, perhaps it’s time for a new package that takes those preferences into account, attracting customers with an offering that perfectly meets their demonstrated needs.

2. Upsell & Cross-Sell

Like Netflix’s and Spotify’s recommendation engines, AI could support businesses in any industry by offering add-on products and services based on offerings that are commonly purchased together and tailored to individual users’ historical behavior. This would not only take the onus off the sales team to identify upsell and cross-sell opportunities, but it would keep customers engaged by consistently offering more value.

3. Update Pricing Models Based on Traffic & Capacity

Aside from recommending products and services, artificial intelligence could use usage data to create reactive pricing models by identifying periods when consumption is generally low (holidays, certain periods in the fiscal quarter or even individual weekdays) and suggesting discounts or incentives to encourage customers to buy. This capability would help keep revenue steady, balance demand and optimize costs-to-serve.

4. Decrease Churn

Finally, an artificial intelligence application could identify patterns that indicate churn and flag users who look like they’re getting ready to end their relationship with the company. That way, a customer service representative would have the opportunity to reach out to gauge the customers’ satisfaction and alleviate any frustrations.

These are just a few of the ways we anticipate artificial intelligence helping clients grow their business through AI-powered intelligent billing. To learn more about how the goTransverse platform can help your organization gain a competitive advantage, contact us at info@gotransverse.com today.

Derrick Snyder is the Vice President of Partnerships and Alliances at goTransverse. Bringing his experience from pricing strategy at Deloitte and big data at National Instruments, we’re pretty sure he might actually be an artificial intelligence system.