Implementing usage-based pricing: What your financial teams need to know

It seems like every article on SaaS pricing these days comes back to the topic of usage-based pricing: whether it’s growing in adoption (it is), whether it boosts important SaaS KPIs like NRR (it does), and whether your company specifically should adopt it (that’s more complicated to answer). 

But the information that is often missing – and yet, is probably the most sought after for Finance teams – is practical guidance: how to actually implement usage-based pricing, what data you need, and how to bill for it.

Here we’ll examine the ingredients for a successful usage-based pricing implementation from a data and process point of view – and with a focus on Finance teams – so you can choose the right tools for the job.

3 ingredients for a successful usage-based pricing implementation (Finance POV)

So, your pricing committee has decided to implement usage-based pricing (UBP), whether it’s a shift to pure-usage based or a hybrid model. There are three ingredients your Finance team will need in order to successfully transfer that pricing strategy to actual customer bills: 

1. Sourcing the right data 
2. Streamlining the usage-based billing process
3. Supporting wider Finance initiatives

1) Sourcing the right data 

The first challenge in implementing a usage-based pricing model (and billing for it) is data sourcing. When a software company begins to move outside the confines of the traditional subscription pricing model – with the addition of elements like allowances, overages, usage, tiers, product add-ons, or custom deals – the number of data points required to make an accurate calculation expands rapidly. 

Implementing usage-based pricing requires companies to aggregate data from a range of systems that feed into the billing process.

One source of truth for account, product, and pricing data

For most businesses, this information will sit in a front-end system, often CRM and CPQ tools, with details captured during the sales process. There can also be specific information siloed in contracts. For usage-based billing, this information needs to be accessible, reliable, and regularly reviewed for accuracy.

Reliable usage data 

Usage data needs to be collected, attributed to customers, normalized, transformed, and stored so it’s ready for your billing cycle. This requires a robust system architecture within your product that can attribute data and usage on a user basis, with clear roles and tags for features and tiers. Pipelines for this data often pull from existing repositories such as a data lake, but modern billing infrastructure solutions can function as a primary collection mechanism for this information. Note that this information can also be valuable to end-customers when tracking their own usage and planning resources.

2) Streamlining the usage-based billing process 

Creating bills from this information requires Finance to combine various data points and formulas in a set process. While some businesses manage this with manual processes and spreadsheets, this can rapidly become untenable as businesses scale and pricing complexities develop. (We covered why manual usage-based billing doesn’t scale in the first article in this Operations your usage-based billing system must be able to perform: 

A. Create billable data

Firstly, usage data needs to be aggregated into figures that can be used during the bill calculation process. This typically involves simple functions such as determining:

• COUNT (how many units of a certain property were there?)
• SUM (what was the aggregate amount of units?)
• MAX (what was the peak of Z?)
• MEAN (what was the average?) 
• UNIQUE (how many unique things were there?)

But there can be additional complexities, particularly if calculations need to be applied on the fly at ingest (e.g., converting kilobytes into megabytes), to combine measurements, or to account for conditionality between them. 

Compound aggregations allow you to flexibly combine consumption metrics for the purposes of billing. Common use cases include dynamic product bundles where a price is applied if a customer uses one or more of the elements of the bundle, or where a product (like an API) can be different for each customer. 

There is also a commercial dimension to how this data should be treated. In the event of exceptions, such as usage spikes, commercial leaders may need to decide if an adjustment needs to be made and how this should affect the account.

B. Apply pricing logic

Once you have the billable data, you then need to apply the pricing model. Pricing models are not always straightforward, and many businesses employ a hybrid pricing model that combines elements of usage-based pricing with traditional subscriptions. Factors that complicate the equation can include:

• Elements of traditional recurring subscriptions
• Volume-based discounts
• Allowances and overages
• One-time fees and standing charges
• Product bundling
• Flexible credit systems such as those deployed by Snowflake

All of these elements combine to create the final price due from your customer, and it can quickly become a complicated process if worked manually.

C. Apply billing and post-rating logic

Once the bill is calculated, there is the task of how to manage that bill and payment. Considerations include:

• Determining when to bill, whether on a set day or linked to the date of subscription
• Billing in advance vs. arrears
• Enabling prepayment and drawdown systems
• Managing discounts across parent and child accounts and charging the right entity
• Applying discounts and credits to bills on an ad hoc basis.

D. Validation and approval

Given the complex processes up to this point, you need the ability to check, validate, and approve bills before they go to customers. Under-billing for usage leads to revenue leakage, while over-billing can undermine customer trust. 

However, any delay in the process can also knock confidence. While you will likely have existing quote-to-cash tooling, this process also requires new components that require integration. For a seamless process, these usage-based pricing integrations need to be easily set up and robust, automatically keeping systems in sync. It’s also a major benefit if non-technical users can manage the integrations, specifically mapping data objects, configuring the system, and syncing processes.  

3) Supporting wider Finance initiatives 

The role of billing goes beyond just getting the right invoice to the right customer. When implementing a UBP strategy, Finance should also have the ability to serve the needs of the rest of the business when it comes to tracking and analyzing revenue at varying levels of detail. (A usage-based billing solution makes this easier.)

Your system of choice must account for:

• Revenue recognition – Planning and tracking revenue in a consumption model is complex, given the frequent variation. This means you will likely need an intermediary step between bill calculation and the posting of revenues to your ledger to assess and normalize the figures.
• KPI tracking – Managing long-term trends requires a standardized approach for KPIs such as Net Revenue Retention (NRR), as well as in-period movements. This also requires a high level of detail to track revenue on a per-segment or per-customer basis and to reconcile revenue movements by period.
• Gross margin analysis – Finance teams often need to track the relationship between revenues, usage, and variable costs to identify under-earning customers and manage long-term profitability.
• Forecasting – Revenues will depend on your future usage, which is uncertain, but the better you can forecast, the better you can plan and communicate with investors and your board. Companies that make conservative rule-of-thumb forecasts in the name of prudence often end up under-investing in their business and missing out on growth opportunities.
• Price optimization – Assessing private pricing deals can be a challenge due to the effect of different prices and structures on customer incentives. The more structured data you can leverage to forecast outcomes based on similar customers, the more confidently you will set and approve custom deals.

Automating your usage-based billing 

Correctly running a usage-based billing process from start to finish involves multiple steps and calculations – the more complex and nuanced your model, the more work required to reach the final bill. However, the majority of these steps can be automated with the right systems in place. 

Tools such as m3ter can work not only as data pipelines between various elements of your stack, but can also store, calculate, and assign charge items with a high degree of detail, reducing the work, risk, and time involved in implementing your usage-based billing workflow.

Our next article, "How m3ter deals with billing complexities for customers", explores how m3ter can resolve these issues in practice to help you build a seamless usage-based billing  process that combines efficiency and control for your Finance team.