The data challenges in usage-based subscriptions

March 2, 2022

Consumption-based subscriptions are a proven way to rapidly grow revenue, but in order to succeed enterprises must tackle the data challenges involved.

Author Andreas Zartmann

The data challenges in usage-based subscriptions

Consumption-based subscriptions and usage-based pricing models are the next logical step for enterprises across all sectors. Why? Well, from a consumer viewpoint, customers now want to use rather than own – in essence, paying for what they actually need on a flexible basis.

The boldest companies are taking note and giving their customers the usage-based pricing they want. And from this they are reaping the rewards: a lower cost of entry to new customers and markets, explosive growth and higher valuations. Plus it’s a more sustainable model for everyone.

And this is apparent everywhere: from how we watch films to how organizations engage with cloud services. (For a deeper understanding of the usage-based business model, take a look at this all-encompassing guide.)

But adopting a consumption-based model is tough. Really tough. There are fundamental changes to make at every level: from selling your services to billing your customers. And fuelling all of these is the most widely-felt challenge there is: data.

So, let’s dig into the challenges that data (and data management) throws up – so you can embark on your journey in a smoother, more seamless way.

Why is data a serious challenge in usage-based subscriptions?

Data is growing exponentially: In fact, usage data volumes have doubled every six months since 2004, according to Forrester Consulting. So when it comes to innovation and modernization of new business models, the need to persistently capture and process massive amounts of data becomes critical. Depending on the service, sources, and offering complexity, this could be tens of thousands of data records instances every minute: an amount that billing systems aren’t built to handle.

Data is dirty and incomplete: It’s not just the volume, it’s the quality of the data too. Data from multiple sources needs to be cleaned, analyzed and made actionable, otherwise billing systems can’t process it – and you end up with billing inaccuracies and revenue leakage.

It comes from multiple sources: With the explosion of digital services and partner-based business models – which leads to more data sources – raw data floods into systems in all different formats. Turning all that into structured data ready for billing and finance systems is a massive undertaking. Plus, the hand-offs between multiple middleware and legacy systems can mean data is lost, siloed, or out of date by the time it hits the billing system.

It needs real-time processing: Usage data needs to be utterly accurate and mapped to the correct customer accounts and exemptions, in as close to real-time as possible. After all, if a customer is being billed on their usage, then this data needs to be available to them in order to understand how their consumption pattern impacts their costs.

It can’t be handled by most quote-to-cash processes: The modern enterprise is a far more complex beast than its shiny user interface might suggest. Every enterprise has dozens of billing systems, CRMs and ERPs that need to work together in harmony, but they are often unable to handle the volume and variety of data produced by digital services.

The fallout of data trouble

If even one or two of these issues are present, the resulting impact on a billing system can spell disaster. The issues look like:

Revenue leakage: You can’t track exactly what your customers use. Which means you’ll almost certainly lose revenue. And the worst bit? You’ll probably have no idea that this is happening (or the extent of it).

Incorrect invoicing for customers and partners: The success of usage-based subscriptions is based on accuracy. If wrong (or estimated) numbers are in play, customers’ trust in you will erode like a sandcastle.

Poor customer experiences: If you’re charging customers on a usage basis, then they need access to how much they have used your product – and crucially, how much they’ve spent. A bigger-than-expected bill can kill your retention rates.

How to proactively tackle these issues

These challenges may seem too much to face when laid out – but this very much isn’t the case.

Rather than an overhaul of the financial skeleton of your business, a purpose-built Usage Data Platform can solve your data challenges and lay the foundations for your business to adopt a usage-based model. It’s an evolution, rather than a costly revolution.

Here’s some more information on usage-based subscription models:

  • This article on Usage-Based Revenue gives you an overview of the model in its entirety: from drivers and challenges, to obstacles and answers.
  • The Guide to Moving to a Usage-Based Model helps you get under the hood of starting this journey – and implementing it in your business. 

Check out our newly launched podcast where we talk about everything related to data for subscriptions.

And if you’d like to chat to us about anything in this blog, we’d love to hear from you. Contact our experts here.

Andreas Zartmann

Andreas Zartmann

CEO @ DigitalRoute
Andreas has extensive hands-on executive experience in software and technology companies – from start-ups to large, publicly traded companies.

He originally joined DigitalRoute in 2012 as CFO, and in 2017 he was appointed as the CEO to spearhead the next phase of the company’s growth. As CEO, Andreas has led the rapid growth of DigitalRoute, as businesses across industries switch from selling products to selling usage-based services, supported by DigitalRoute’s Usage Data Platform. For more than 20 years, the platform has enabled businesses to track and orchestrate usage data, turning raw data into new revenue streams.

Prior to DigitalRoute, Andreas held key executive roles as CFO at various information technology and telecom companies, as well as in investment banking and management consulting. He holds a master’s degree in business administration from Linköping University, Sweden.