Data for subscriptions podcast - Episode #3
Mastering the Business of Subscriptions
CEO at DigitalRoute
CEO at DigitalRoute
The subscription industry is moving to a new phase. Businesses are shifting from a flat subscription fee to usage-based pricing, something that the telecom industry has been doing for a long time. But this shift comes with many challenges.
In this episode of The Data for Subscriptions podcast, host Behdad Banian speaks to Andreas Zartmann, CEO at DigitalRoute, about the challenges businesses may face in this period and how they can emulate the telecom industry to overcome them.
Well, that’s a pretty big question, let me try to give you a simple answer. In the last 10 years, the subscription industry grew rapidly from low volumes. Most companies had simple business plans where subscribers paid a flat rate.
But that model was largely limited to the B2C sector. In the next phase, we can expect a B2B boom with more complex usage-based pricing and business models.
They have built their tech stack for both large volumes and complexity of data. With this, they’re able to easily tap into new revenue pockets. For instance, most telecom providers have around 600 to 700 pricing plans, in the form of postpaid, prepaid, family bundles, and others.
For companies to move into the next phase and continue to grow their subscriber base, they have to build their systems to scale in terms of both volume and complexity as in the telecom industry.
Usage data is at the very core of the revenue for the subscription model. It plays a huge role in how customers and companies communicate. It’s how we package services and create revenue streams. In many companies, revenue loss due to data leakage can be from 10% to 15%, even though many think it’s somewhere around 2% to 3%.
It’s essential to understand that usage data doesn’t come for free. This is something that you need to, first of all, go and collect from different disparate systems. And you need to put together this usage data record. And most of the time it comes out with errors.
So you need to process and enrich this data record to get the quality that the application billing system needs to do its job. And then when we talk about data in general, it could be any data flowing through the operational systems.
Here, you’re working on transaction data and companies have to get it absolutely right. If the invoice is wrong or is perceived as wrong, they’ll have to go back and show the customer how they were billed.
And this is a complex process, you have to collect the data, process it, enrich it, communicate it to the end application, and build a full quote to cash process. And generic data integration tools just can’t do them at scale. You need a purpose-built solution.