In this article…
In Part 1 we described how early-stage SaaS businesses with UBP and PLG models often found the need to invest early in developing data infrastructure solutions to automate their billing and reporting operations, and the unexpectedly high cost of doing that in-house.
If taking the in-house route, as these projects deliver - typically owned by Product or Finance - you think you’ve got it sorted. Better yet, you’re moving up in the world, starting to attract the attention of Enterprise customers with your product. And that’s when you discover a sting in the tail: adding Sales-led motions to your mix multiplies the complexity.
When it comes to UBP, as soon as you get over a certain size and start serving Enterprise customers, your needs will shift dramatically. Not only will you need a sales team equipped with the right data and tools, and you’ll find your dreams of simple one-size-fits-all pricing shattered upon contact with the first procurement team. Even if you can standardize on the measures you use to price on (not a given), it’s conceivable every customer over a certain size will have a customized element to their deal. The most commonplace complications will be commitments, pre-payments, custom inclusive usage allowances, and bundles of differently-measured and priced products. A key benefit of Sales-led is commercial innovation and flexibility to win deals, but this has operational implications.
UBP especially allows for nearly infinite variety not only in what you base pricing on, but how you price. How do you deal with this growing complexity? You can’t keep expanding spreadsheets or coding for every new pricing model customers want; if you keep changing the shape of your data every time you innovate pricing it will become useless for the analytics and reporting all growing businesses need to manage things like forecasting, profitability and financial compliance.
To deal with this complexity, you need a data infrastructure created to handle usage-based models as well as seat-based and subscriptions; a data model designed from the ground up to accept any usage, cost and price data, transform them into a format that will allow you to meter anything, rate at scale, and the use the same data for analytics.
The secret of m³ter is that we never saw usage-based pricing and billing as just a giant calculator problem (although we are very proud of the giant calculator we have built!). This begins as a data problem, so we started not with that calculator, but with the data infrastructure – creating a unique usage, cost and pricing data model.
m3ter uses advanced anchor modeling techniques for every event to transform data into a ‘6th normal form’ database. This abstraction allows the data to be re-used for a myriad of different purposes, rather than being tied to a single use case (e.g., calculating bill totals). It supports use cases across the whole operational AND analytical spectrum, from providing the aggregated input to the billing calculator, allowing exploration for forensics and reconciliations, to providing cleaned, integrated and structured data needed for business intelligence and advanced analytics such as revenue forecasting, cost allocation, price optimisation, and customer segmentation.
The way we transform and persist data creates a unique, flexible and reusable format. Using m³ter to solve for your billing operations needs effectively creates a specialized usage, cost and pricing data model that is automagically bespoke to your product and usage models, but that you never have to design and maintain yourself.
m3ter persists a canonical data model of your customers’ usage, your costs and your pricing - letting you break down data silos within your business and ensuring not only accurate bills (and happy customers!) but also powerful strategic insight throughout your quote-to-cash stack and beyond.
Ready to deploy usage-based pricing, set up some time to talk to our team.