Data for subscriptions podcast - Episode #4
The journey to usage
CTO at DigitalRoute
CTO at DigitalRoute
Shifting from a flat-fee subscription model to usage-based pricing is not an easy task to undertake. But mastering service usage data can make that evolution faster, easier, and more profitable.
In this episode, host Behdad Banian is joined by DigitalRoute CTO Demed L’Her to discuss how to build robust billing systems for the new model and the journey to get maximum value out of usage-based pricing.
You’ll find yourself in a lot of trouble if you don’t know what users are doing with the services you’re implementing. Without usage data, you won’t know if you’re leaking revenue, you won’t know if you’re pricing your services right and if your customers are actually using your services.
Now, you might be thinking, some of the subscription services charge a flat fee, so why should they worry about usage data? Well for them, the usage data is important for settlement.
Even if you’re charging a flat fee for a package of services, say a library of movies, you’ll have to pay the cost to the service creators for how much the end user is consuming. For a library of movies, you’ll have to pay a royalty based on the number of streams each of them is getting.
So, there are mainly two segments of customers that we see. One is large businesses in telecommunications, as well as cloud providers and the like. The second category is smaller businesses that offer more specialized services.
When these large companies approach us, they’re looking for flexibility in their systems. They have homegrown systems to manage their billing and operations, but they don’t have the flexibility that the new models need.
With smaller companies, they often don’t even realize that they have a data problem.
A lot of people are not going to like this, but focus on the data problem first. Focus on getting good clean data and well-packaged data for your billing system. Once you’ve got this right, focus on the billing system.
Because, to an extent, you can make even an old billing system work for your new solution. You’ll have to change it at a later point, but by getting the data transformation right, you’ll have an easier time fixing the billing. The billing system will have to handle a massive amount of data and it should be able to scale to that. When companies try to build a brand-new billing system first, they realize that they have a data problem.
I’m talking about billions of events per day. To give you an idea, our platform supports the largest mobile operator in India today with millions of subscribers. Every single text message sent on their platform hits our systems and we process it, digest it, summarize it, and give it in a proper and clean way to the billing system.
Sure, but it’s important that everyone understands this is not exactly a map you have to follow step by step. Sure some of the first steps would be more or less the same for most companies, but then it really depends on what you’re trying to do.
The first thing is to connect to your production systems, for instance, your video servers or IoT platforms. Once you have the raw data, you need to put some context or color on it.
Once you have that, we should start looking for some insights from this and try to see what the data is saying.
The next thing we need is to put a monetary value to this and for this, we need this data in buckets based on usage. And we assign values to these buckets.
Next, is what we call revenue assurance. If you get this right, you more or less get this entire process done free for you. This is where you look for revenue leakage and plug those holes.
The next step is entitlement and it’s mostly for businesses that want a more refined business model. This is where we try to build different pricing plans for the company. The last step is to figure out the settlements.