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Usage-based Pricing with IoT Data: Building your Competitive Advantage

When tech leaders talk about innovation, what do you think? Self-driving electric cars? Keynote-presenting, turtleneck-wearing founders? The blockchain? Usage-based Pricing models probably aren’t the first thing that comes to mind as a product leader, but they should be—especially if you work in manufacturing and provide high-tech devices for automotive, healthcare, computing, or any other manufacturing segment.

The truth is, pricing models are an excellent innovation opportunity for manufacturers, but most people don’t consider them first when they think of innovation.Take usage-based pricing with IoT data, for example. It’s basically been on everyone’s radar since 2011, when we first heard about Industry 4.0—but the model is only now beginning to become commonplace. The premise is simple: companies use IoT devices to gather usage data straight from their customers, which informs how much they must pay, among other things.

Imagine an automotive manufacturer, for example. They might use IoT data to monitor their factory floor, with interconnected devices made by you. These devices collect data on how much each machine is used, for how long, when, and how it’s performing. These datapoints can then reduce human intervention by enabling predictive maintenance, highlighting when a machine is about to break before it does. Additionally, the same usage data can also dictate how much a company must pay (the more you use a machine or service, the more you pay).

Pretty cool, right?

Below, we outline how some innovative companies already use this model to their advantage, explain why it benefits customers and businesses alike, and explore how billing and monetization software facilitates these models. Finally, we’ll provide some arguments for you to use when convincing your prospects and customers of the value of usage-based pricing with IoT data. By considering the points listed below and rolling out usage-based pricing for your customers, you’ll carve out a tangible competitive advantage for your business.

Here’s how.

Successful IoT data-driven business models

If you’re uncertain quite what an IoT data-driven business model can be, check out the examples below, which outline how innovative companies can use IoT data to provide flexible billing options for their clients in 2022.

Coffee Machines

First, let’s start off with an easy example. Imagine you manufacture coffee machines. Your customers (cafes/coffee shops) purchase one of your machines for a nominal fee—or perhaps they might even receive it for free. However, they are charged on a monthly basis from then on, based on how many cups they brew. The more cups they brew, the more they pay.

So, how exactly does this work?

IoT sensors collect each machine’s data and send it over to your IoT platform, where it’s then converted into usage data (e.g. cups brewed). This data is then sent to your billing and monetization software (like Nitrobox) where it’s converted to billable data. Finally, customers are invoiced according to how many cups they brewed. Check out the graphic below for a visual representation of this process in action.

 

 

Siemens

SIMATIC Energy Manager 

SIMATIC Energy Manager is an IoT-based company-wide energy management tool that allows companies to visualize detailed energy flows and consumption values in their processes, assign them to the relevant consumers or cost centers, and identify why changes have occurred. Customers are charged via a usage-based pricing model, with IoT data informing Siemens how much customers used the tool per month. 

 

Siemens Healthineers

Likewise, Siemens Healthineers utilizes IoMT (the Internet of Medical Things) to offer usage-based pricing, delivering “more coordinated, continuous care that is location-agnostic and more cooperative”. For example, its Performance TOP SMART and Advance MAX SMART service plans for medical equipment follow a “smart financing model based on your scan throughput”—meaning the more customers use the tool, the more they pay.

Heidelberg printing

Each Heidelberg printer contains over 3,000 IoT sensors. Each sensor collects data on the machine and its processes before sending this through to the Heidelberg Cloud, which connects over 13,000 machines and 25,000 software modules.

Heidelberg adopts a mixed billing model, charging customers a regular subscription for the machine with an added pay-per-output element for how much they use the machine. This means customers pay a fixed monthly charge as well as an additional fee depending on their output (e.g. printed sheets), with those that print more paying a greater fee than customers who don’t print as much.

Bosch

Another example of a German giant leading the charge on IoT adoption (the direct result of industry 4.0 kicking off over 10 years ago), Bosch established a join German-Chinese venture in 2018 to create a IoT-driven manufacturing facility. In the Wuxi-based factory, Bosch automotive diesel systems manufactures high efficiency, low emission diesel engine parts. Bosch used big data and IoT interconnectivity to redesign the factory, allowing them to better understand and eliminate output losses and enable predictive maintenance. 

The challenges of adopting a usage-based pricing model

Despite the clearly demonstrated benefits of adopting a usage-based pricing model based on IoT data, there are a few potential hurdles to overcome. However, don’t let these put you off—knowing is half the battle. Here are some common challenges you might face as you start to build out your next big thing.

Up-front cost

IoT interconnectivity is still often a price barrier for many. A key challenge you’ll need to wrangle isn’t installations, software updates, or general implementation headaches. It’s determining if your business fits into an IoT and big-data driven pricing strategy. Usage-based IoT pricing necessitates that your offerings be physical devices, like the above examples. These devices need to be built to enable IoT connectivity, and depending on your manufacturing methods, this could be a problem.

Getting customers on board 

Next, convincing customers of the value of adopting your IoT devices and adjusted pricing model. Flat fee structures are easy to understand and easy to budget, and don’t require as much implementation effort. Usage-based pricing, however, is viewed with a lot more uncertainty. Companies may not have internal processes to determine usage, maybe just relying on how much electricity they use. They may not believe in the pay off, which is that usage-based pricing with IoT data, in the long-term, is more affordable. They also just might not have the cash on hand to make the change. You’ll need to address these pain points. 

Your usage-based pricing must be meticulously crafted by prioritizing the users’/customers’ interests. If you can’t justify how the model benefits end-users, customers might be put off by its lack of certainty.

Picking the right metrics to price

Companies must select the appropriate value metric to price their customers’ usage. Ideally, this metric should align with their products’ value proposition—hence why Heidelberg chooses “printed sheets”. Pick a scalable metric that correlates to customers’ value and is easily measurable by IoT devices. Know that you don’t have to commit to one metric forever. Changing and adjusting what you measure is an essential part of fully grasping IoT data.

Implementing a usage-based model across your systems

Updating your hardware to be IoT-enabled is just one part of the story—unfortunately, software can often be a critical bottleneck. Many billing and monetization software providers (especially legacy ERP providers) can’t account for usage-based pricing models.

The problems are as follows.

Companies that have traditionally sent their customer’s large invoices on an infrequent basis now have to regularly produce multiple invoices for small amounts. If their customers operate globally then the manufacturer must send out invoices in several different currencies, further muddying the waters. Legacy billing systems aren’t built for this complexity—meaning finance teams struggle to make this billing model work, no matter how hard they try.

This is where Nitrobox comes in. Nitrobox converts machine data into billable data depending on the required billing cycle (days, months, etc.), and automatically creates all invoices and credit notes. Our platform seamlessly handles any number of machines, in any country or currency, and can process millions of transactions simultaneously.

In other words, we can help you transform your business and turn IoT data into new revenue streams. We offer enterprise-class software designed from the ground up to enable usage-based pricing, and IoT data is easy to integrate into our software.

The benefits of adopting a usage-based pricing, IoT data-driven model

Because of improvements to hardware and software, getting started with usage-based pricing in manufacturing isn’t as difficult as it was just a few years ago. First, businesses are more aware of the model and looking to adopt it to drive customer value and differentiate themselves. Second, innovative billing and monetization software (like Nitrobox) makes it easier to roll out (and manage) from an infrastructural perspective. 

Nitrobox was built to help companies roll out new monetization strategies in weeks, not months, integrating directly into backend systems such as SAP. Rather than creating more complexity, tools like Nitrobox help businesses organize and structure the wealth of usage data that comes in.

You might be thinking “Sure, that’s all well and good, but what’s in it for my customers?”. We mentioned above one of the challenges would be getting them on board. When implemented properly, usage-based pricing using IoT data is incredibly beneficial to your end users—here’s a few arguments to use to offer IoT-driven usage-based pricing to your current and prospective customers.

An innovative, customer-centric approach

Using IoT data to power a usage-based billing model will set your company apart from competitors. It’s a critical differentiator that shows you’re willing to adapt your own operations (e.g. how much you charge for your services) around your customers’ varying needs. With usage-based pricing based on IoT data, customers control of how much they pay—not your company. Additionally, you’ll be offering them technology to improve their own business.

It’s worth noting that this billing model will fundamentally change the nature of your customer relationships. When you charge customers a one-off fee (e.g. for a coffee machine), the relationship essentially ends once they convert. When you regularly bill customers based on their usage, however, you’ll maintain an ongoing relationship with them—which will help establish a sense of loyalty. You can even use their IoT usage data to upsell them (and improve their own operations), suggesting additional machinery/services based on how their business is performing.

In fact, following a usage-based billing model will likely make it easier to sell to customers in the first place. Purchasing your machinery/services will no longer be a one-time, large, harder to justify Capex—instead, it will become a smaller, more regular Opex.

Scalability

With IoT data at their fingertips, your customers can scale due to dramatic increases in efficiency. Your benefit is you have a data-driven pricing plan that can scale, too. You’re never going to end up in awkward situations where your customers are locked out of certain features because they’ve paid for a “basic plan.” If they ever need to drastically ramp up the amount they use your product (and the particular features they require), they can do so without any hassle.

Flexibility

Customers gain greater control over how much they spend each week, month, and year. If they’re going through a quiet period, they’ll pay less. If business suddenly ramps up and they need to use the software more often, they’ll pay more.

Fairness

Usage-based pricing models are inherently designed to be fair. That’s what software companies like us believe, at least. Users aren’t locked into contracts that don’t reflect the true value they gain from using an up-to-date piece of machinery. Instead, the amount they pay is directly linked to how beneficial the software is for them. Following a fair and logical billing model will work wonders when it comes to increasing customer loyalty. Most times, today at least, there is a hybrid billing model agreed upon to drive the most value for the customer. This wasn’t possible 10 years ago.

Caters to all customers

Usage-based pricing provides customers with customizable billing options suitable for various needs and budgets. They don’t have to settle for pre-defined, rigid “basic”, “intermediate”, or “advanced” plans—instead, they just pay what they use and get the advantage of using IoT-connected devices themselves. It’s a win-win. 

An innovation you can’t ignore

Usage-based pricing with IoT data is only going to become more common, thanks to the proliferation of IoT devices combined with customers’ willingness to pay only what they owe (and not a cent more), and their desire to use modern technology to improve their own business.

Companies that move quickly will separate themselves from the competition, proving they’re customer-first and innovative. Those that fall behind the curve, however, will find themselves playing catch up. We’re well past the early adopter phase in many manufacturing industries, so if you’re not on the bandwagon yet, now is the time. We’re not quite yet at mass adoption, but the floor is shrinking. There’re also many industries that still can stand to benefit from IoT connectivity, like home appliances. Many IoT-connected home appliances are available, but the pricing on them is still very restrictive. Or appliances for restaurants. Just look at our example above.

Get ahead of the game by implementing IoT-based pricing as soon as possible, using tools like Nitrobox to manage all usage-based data and billing matters from a single source of truth. To find out more about how Nitrobox powers usage-based pricing with IoT data, get in touch to arrange a free trial of our platform.