How to calculate and track key SaaS performance metrics for usage-based pricing models

SaaS companies everywhere have witnessed a massive shift in customer expectations in recent years. Today, customers now want more flexible, transparent, and value-driven solutions for their specific business needs. They only want to pay for what they use, and they don’t want to be “locked” into a service with rigid or long-term contracts. 

Usage-based pricing models answer this demand because they directly relate the cost of a SaaS product to its usage. Simply put, as a customer, if you use or consume more, you pay more, and vice versa. From a service provider’s perspective, such models allow companies to take a more customer-centric approach to deliver an optimal customer experience while at the same time, creating a more stable revenue stream from existing customers. 

Usage-based pricing also makes your SaaS product more accessible to users, as they can start with a lower entry cost and scale up as their business needs grow. The incorporation of usage-based pricing models by traditional subscription-based companies reflects this changing landscape of SaaS pricing models.

However, the variability inherent in usage-based pricing makes predictability in revenue more challenging to achieve. It also makes applying key SaaS metrics, such as ARR, NRR, gross margin, and customer LTV more complex. 

This article explores the history and evolution of subscription-based models to usage-based pricing models, discusses the three main types of pricing models, and illustrates (with examples) how to apply key SaaS metrics to a usage-based pricing model to measure and track performance. 

A brief history of usage-based pricing  

Every company today uses a lot of SaaS tools. The number of SaaS apps used by organizations worldwide grew exponentially, from 80 in 2015 to an average of 130 apps in 2022. By 2023, SaaS adoption had increased to 371 SaaS applications used by an average company. 

Thirty years ago, most technology products (excluding on-premise solutions or one-time fee approaches) were subscription-based businesses with a set monthly fee. On-premise solutions naturally came with a high total cost of ownership (TCO), which included expensive hardware, complex installations and maintenance of servers, and frequent software updates. Given this, larger enterprises were more able to make these investments whereas smaller businesses were less able to afford them.  

In the early 2000s, Salesforce created a paradigm shift and was the forerunner for the software-as-a-service (SaaS) industry—making the case for on-demand software and eliminating the need for extensive in-house hardware. Given the unpredictability of revenue, investors were naturally skeptical of this pioneering business model. 

Salesforce’s objective was to remove all up-front payments from customers and replace them with monthly payments (or the “pay-as-you-go” approach) for access to the software solution. Smaller businesses now could easily access and afford the SaaS technology they needed, e.g., emails, CRM, and messaging tools. 

However, monthly billing became a huge challenge for accounting teams as they had to generate invoices for each and every customer for payments. So, vendors started shifting from monthly contracts to annual contracts and eventually multi-year contracts, making revenue more predictable while also making it very convenient for customers to stick to one service provider for their business needs.  

As customer needs evolved, the seat-based model—wherein businesses pay for the number of accounts/licenses—also began to pose difficulties for users because seats (licenses, accounts, etc.) would often go unused, resulting in customers paying for more than they really needed.  The shift to usage-based models solved this problem but introduced new complexities, particularly in billing customers and forecasting revenue. 

The point is, variability is inherent in any consumption-based model and that’s the reality for many SaaS companies today. As a SaaS business leader, you need to understand it, accept it, and embrace it, to ensure your company is able to achieve its planned growth. This article will help you do all that. 

Understanding the three main types of SaaS pricing models 

Within the highly complex world of SaaS pricing, the word “subscription” can mean different things to different people. So, for the purposes of this article, we have broadly explored three different pricing models, namely, subscription-based, usage-based, and hybrid. 

Subscription-based pricing

Subscription-based pricing, also known as “flat-rate” pricing, is a plan where customers pay a recurring fee on a monthly or annual basis to access products and services. These payments provide customers with ongoing value since they can use the product over an extended period rather than purchasing it once. Flat-rate pricing works best for products and services that customers use regularly and don’t necessarily need more than what they pay for.

This pricing model has been a mainstay in the SaaS industry since its inception and is still widely used today. This is probably because for a SaaS business, flat-rate pricing is a lot simpler than almost any other pricing model out there, which makes business financial processes, such as billing, accounting, and forecasting easier. 

Subscription-based pricing also provides businesses with better control over their revenue by enabling them to forecast future income from existing customers. Given the ease of billing and payments, it helps SaaS companies differentiate from competitors and reduce customer churn. On the other hand, customers benefit from low-cost access to the necessary services and the convenience of monthly payment plans.

However, a potential downside is that with a purely subscription-based model, growth is dependent entirely on winning new customers and/or raising prices, which is never popular with customers.  

Usage-based pricing

Usage-based pricing (also known as consumption-based pricing, pay-per-use pricing, and pay-as-you-go pricing) is a pricing model where customers pay for a product or service based on how much they use it. As a result, revenue will almost always vary from month to month. 

Usage-based pricing adapts to customers’ individual needs, allowing them to pay less when they use less and more as their usage increases. This flexibility not only makes it easier for new customers to adopt a product due to lower initial costs but also encourages existing customers to explore and utilize the software more comprehensively. Such engagement often leads to discovering new use cases, enhancing customer satisfaction, and ultimately, increasing customer lifetime value.

The different types of usage-based pricing models include:

• Per-unit usage pricing: As the name suggests, usage-based pricing is a pricing model in which price varies based on how many “units” of product a customer uses or consumes, rather than charging them for the amount of time they have the service active. This means that customers who consume more will pay more, and vice versa. Companies can define their units of pricing in any number of ways, such as the number of seats or features a customer uses, the amount of cloud storage or compute, etc., based on their unique pricing model. 

• Tiered pricing: Usage-based tiers constitute a fixed price the customer pays for a fixed allowance of units for the period they have chosen. For any additional units consumed, customers are charged overages. With this model, your customers’ subscriptions are adjusted or right-sized based on tiers or bands of usage. Tiered pricing can help garner more customers by incentivizing them to use your product or service in greater amounts.

• Volume pricing: Volume-based pricing is basically a declining price per unit against increasing volume. The more you consume, the less you pay for each unit. Volume pricing is a great strategy for encouraging customers to buy more products by offering discounts when they do. This creates greater value for their money, and they're more likely to buy your product or service. 

Usage-based pricing can be found across the SaaS stack, from infrastructure through applications. In fact, usage-based pricing seems to be the second most popular pricing model after subscription-based pricing. 

Hybrid pricing

Hybrid pricing is a strategy that combines two or more pricing models discussed above within a single plan. This might be a combination of two or more usage-based pricing components or combination of a subscription fee with a usage-based component. Or, it could be a combination of subscription fees — basically some minimum amount the customer will be charged regardless of their usage or the usage-based components (agreed upon)—along with defined usage-based components. 

This mix-and-match approach allows SaaS companies to cater to multiple customer profiles by offering different pricing metrics and options (e.g., basic, premium, enterprise, etc.) within a single package. By closely mapping and scaling pricing with customer-perceived value, a hybrid pricing model leads to increased conversions and customer retention. 

While it may seem like splitting hairs to describe this type of model as a hybrid when the majority of components are usage-based, such models introduce far more complexity than those that involve a single usage-based component and probably more than any other type of pricing model out there. 

The key thing to remember about hybrid pricing models is that they can be highly complex, which of course, can make measuring and tracking their performance quite difficult. 

Benefits of usage-based pricing

Usage-based pricing works particularly well for both vendors and customers as it links costs to value received and allows fees to scale as customers grow. While this pricing model may not be applicable to all businesses, for those SaaS companies that do use it, the benefits can be significant. Let’s take take a look:

• Enables easier adoption: Potential customers face fewer barriers and minimal upfront costs with usage-based pricing, reducing capacity estimation requirements, stress, even the fear of money loss. Easier adoption means that SaaS vendors are able to evaluate what works well as they expand their market reach. Further, the lowered barrier to entry attracts more customers to get started and allows for a subset of customers to grow their usage rapidly.
• Ensures costless upsell: Usage-based pricing presents an opportunity for companies to deliver greater value to the customer and pursue product-led growth (PLG), creating opportunities to grow revenue without additional effort from the sales team. The sales team can now continue to focus on value-adding activities, such as securing commitments, facilitating adoption, and looking for new business.
• Enhances customer satisfaction: Many customers report that usage-based pricing ensures better alignment with the value received when paying based on their consumption. Customers don’t have to worry about shelfware, or wasteful spending and are able to optimize their product usage. 
• Improves margin control: For SaaS companies with significant costs driven by customer usage, usage-based pricing helps them gain tighter control over margins. The right pricing metric can link revenue and costs to usage, improving consistency of unit economics per customer. Companies that implement usage-based pricing models tend to see higher LTV and lower CAC payback period— this means faster growth and higher valuations from investors.
• Increases customer lifetime value (LTV): A key differentiator for usage-based pricing  versus other pricing models is that SaaS businesses that use it typically don’t limit the number of users who have access to their software. This drives customers to discover new use cases, leading to long-term success and a higher customer LTV.
• Increases NRR: Net revenue retention (NRR) is a key metric to measure the success of the usage-based pricing strategy. Businesses with a usage-based pricing model  typically see higher NRR than those that don’t.

How is usage-based revenue calculated? 

Usage-based pricing models do not map cleanly to the monthly recurring revenue model that most subscription pricing businesses in the SaaS industry use. Nonetheless, many consumption-driven businesses do report their usage-based revenue as annual recurring revenue (or some version of it). 

Annual recurring revenue (ARR) is a SaaS metric that tracks the recurring revenue gained from subscriptions, normalized for a single calendar year. However, with usage-based pricing, calculating ARR can become very complicated. 

Ideally, all recurring revenue needs to be considered when calculating ARR. Recurring revenue is revenue that is generated from subscriptions that are charged at regular intervals, which may be every week, month, or year. This type of revenue is steady, predictable, and can be scaled up over time. 

In contrast, the revenue generated from usage-based pricing models isn’t really recurring revenue. While many companies with usage-based pricing models treat this revenue as ARR, we draw a distinction between ARR and usage-based revenue because with usage-based pricing, customers have the ability to vary their consumption. Therefore, the usage-based revenue you’re generating may or may not recur. 

To gain a better understanding of this distinction, let’s first look at the formula for the more traditional, subscription-based ARR where customers pay a monthly flat fee:  

Now, let’s look at a formula for calculating revenue for a hybrid pricing model, which includes both recurring, subscription-based revenue (ARR) and variable, usage-based revenue. 

Let’s understand the terms:

• Beginning ARR: ARR at the start of a specific period, e.g., fiscal year, quarter, etc.
• Ending ARR: ARR at the end of the above-mentioned specific period (which becomes the beginning ARR for the following time period
• New ARR: New subscriptions
• Expansion ARR: Subscription upgrades
• Variable revenue: Additional revenue generated from the usage-based components of pricing, which includes any overages or shrinkage in usage.
• Contraction ARR: Downgraded subscriptions
• Churn ARR: Canceled subscriptions

Keep in mind that minimum commitment is the revenue that a SaaS company will receive from a customer (contractually guaranteed), even when their usage is below the agreed minimum threshold. This ensures a baseline of recurring revenue. Hence, in the above formula, New ARR, Expansion ARR, Contraction ARR, and Churn ARR pertain only to the minimum commitment revenue as that's the only predictable component (the only ARR).

Once you understand how to calculate your ending ARR for usage-based pricing each month, you can model it going forward with a basic corkscrew model, wherein the ending ARR for the current month will become the starting ARR for the following month. 

How usage-based pricing affects other SaaS metrics

Most SaaS metrics are built upon the assumption that a customer, or cohort of customers, produces a known (predictable) ARR. In usage-based pricing, there is higher variability in predicting revenue due to the fluctuations around customer usage. Therefore, it becomes all the more complicated to measure and track revenue, especially when in a hybrid model that can have a mix of fixed and usage-based components. 

If your SaaS business employs a usage-based model, in order to calculate reliable performance metrics, you’ll need to tackle that with your first-order metrics because the difficulties that variable pricing introduces will magnify as you incorporate your results into second- and third-order metrics.  

Some metrics will be unique to your usage-based pricing. However, you may need to add a couple of additional metrics to your mix to more accurately capture performance. 

Let’s take a look now at how you would calculate three key SaaS performance metrics – NRR, gross margin, and customer LTV – with a usage-based pricing model.  

Calculating and tracking NRR with usage-based pricing

Generally speaking, NRR is higher in any consumption-based SaaS business than it would be in a purely subscription-based business. This makes sense because expansion is built into it by design, and this expansion helps drive higher and more profitable growth.  

While usage-based pricing has become very attractive to SaaS businesses, it does complicate the process of calculating and tracking NRR. 

To give you a sense of the complexity, let’s say you wish to calculate NRR for the cohort of new customers that signed up in January. Calculating NRR for the January cohort is pretty straightforward with a subscription-based model. To get the starting ARR, you simply multiply the number of customers in the cohort by the subscription price. 

However, with usage-based pricing, it’s highly likely that within the first month, one or more of those customers from the January cohort will expand their usage. In this case:

• How would you account for the ARR associated with that increased usage? 
• Is it part of the initial ARR or should you consider it expansion ARR?

When you look at the NRR formula below, it’s easy to see mathematically how your decision can impact your results. If you consider that expansion as part of the ARR at the start of the year, your NRR will be lower than it would be if you treat it as Expansion ARR. 

The variability inherent in a usage-based pricing model also makes tracking and plotting NRR month over month even more complicated. To understand why, let’s consider another example. 

In Month one, you have $100,000. In Month 2, it’s $120,000 due to increased usage, a 20% expansion. But, in Month 3, the ARR from that cohort drops to $80,000. You expanded by 20% in the second month, decreased by $40,000 in the third month, which is 33%. 

So, how do you figure out your rolling three-month NRR? 

Use a look-back window

You can use a two-year look back window, comparing revenue from each customer over the last 12 months to the revenue from the previous 12 months—for a total of 24 months’ of data. 

This creates a two-year lag in measurement, which helps even out all the variations that arise as a result of seasonality and usage-based pricing to provide a somewhat more consistent number. 

Define a ramp-up period

Another approach to measuring NRR with usage-based pricing is to define a ramp-up period based on the customer’s usage in the first month. 

For example, if you know that your customers typically expand their usage in the first 45 days from $100 to $150, you can use the revenue from the first 45 days (as opposed to the first month) as your starting ARR. Then, after that 45-day ramp-up period, all the revenue above and beyond the initial revenue will be considered expansion ARR. With this approach, it’s useful for the purposes of clarity to describe your ramp-up in terms of the “number of days from initial use.” 

Note that it’s very important to be consistent in how you define your ramp-up and use it uniformly across all cohorts even if your data for later cohorts suggests that it has changed. While this may seem counterintuitive, you must apply your ramp-up time the same way going forward from the first cohort it’s based on because changing your ramp-up period from cohort to cohort will fundamentally change the calculation, making your NRR results unreliable (as a whole).  

If you do feel compelled to change your ramp-up period, you can do that as long as you go back and apply it to your past NRR calculations and inform all stakeholders about the change you made and why. This transparency will help you avoid any perception of metrics manipulation.    

Calculating and tracking gross margin with usage-based pricing

Usage-based pricing can also impact your gross margin as a function of your company’s cost of goods sold (COGS). To understand this, consider the gross margin equation:

COGS includes variable costs that increase in proportion to business growth. This means that as your revenue grows, your COGS grows right along with it. So, there’s already a lot of variability inherent in your gross margin. Variability is the price you pay to ensure frictionless growth (in a manner of speaking). As a result, you don’t have a consistent number for the gross margin. 

Let’s look at the variability in the context of all the new customers you gained in the previous month. Your revenue from that cohort of customers is $100,000 for the first month and on average, your customer usage is growing about 2% each month. If you assume that the revenue from all those customers will continue to grow at that same rate for 24 months, you can calculate your monthly recurring revenue (MRR). 

Here, you also have to factor in a gross retention rate. So, let’s assume that you will retain 90% of your customers from the cohort. Now, with your MRR and gross retention rate figured out—and based on your assumptions—you should be able to determine the COGS and then calculate your gross margin. 

The problem is that your assumptions, particularly those regarding usage, may not hold. Remember that with usage-based pricing, variability in usage (and thus revenue) is typically very high and harder to predict. Your MRR is continually expanding when you have a usage-based pricing model, and as a result, your gross margin will be even more inconsistent from month-to-month, even quarter-to-quarter.

Calculating and tracking customer LTV with usage-based pricing 

The problems associated with calculating a reliable gross margin when you have usage-based pricing also makes it more difficult to calculate customer lifetime value (LTV). This is because gross margin is part of the LTV equation: 

While your churn rate may be somewhat consistent, your gross margin and average MRR per customer must necessarily be based on assumptions that can be extremely difficult to accurately predict with the variability built into usage-based pricing. To the extent that any of the variables in your calculation are off, your results will be less reliable. 

Keep in mind that if you see that your customer usage patterns are somewhat consistently growing with revenue over time, you can use historical cohort data to derive a revenue trend that is perhaps more reliable. However, the variability in gross margin will still impact your results.    

Leveraging technology with usage-based pricing for better performance tracking

With all the benefits that usage-based pricing offers for SaaS companies, it’s small wonder that more and more companies today are optimizing their pricing structures with the addition of usage-based components.

But in addition to those benefits, for the growing number of businesses that are shifting to a usage-based (or hybrid using a combination of subscription and usage-based) pricing model, there’s a corresponding cost in terms of the complexity it introduces into tracking standard SaaS metrics.

Usage-based pricing makes key SaaS metrics like ARR, NRR, gross margin, and LTV trickier to calculate because it doesn’t play by the traditional rules of subscription-based pricing upon which most SaaS metrics were constructed. 

Navigating these challenges can be simplified, however, with a financial planning and analysis (FP&A) solution that can serve as a single source of truth for all of this information. Additionally, these tools automate the data validation process, empowering finance professionals the power to build whatever models they need for financial forecasting.

‍Drivetrain is a purpose-built, strategic FP&A software that seamlessly integrates with different systems and apps, and consolidates all the necessary data, in real time, on a central, user-friendly platform. The platform offers a host of features that can help you navigate the complexities of measuring and tracking the revenue obtained from using a consumption/usage-based or even a hybrid pricing model—to make sure your forecasts are more accurate. Here are a few relevant ones:

• Integrations: With over 200 integrations, Drivetrain can easily collate and access all the data and variables you need from different sources (e.g., QuickBooks, NetSuite, etc.) to perform a granular analysis of usage in a very automated manner. You can even slice and dice that data to analyze the trends around usage, churn, and expansion across all customers. 

• Formula creation: Drivetrain’s formula builder is straightforward and intuitive, enabling you to write formulas across multiple dimensions for a metric. It easily takes the values from the previous quarter (or your defined time period) and encapsulates the varied definitions for the same metric to prevent any errors, thereby helping users build more robust financial models. Drivetrain also isn’t limited to standardized formulas. To understand the different usage-based components of your revenue along with any ARR, you can easily create formulas that will adapt to any changes in the reference data (something that isn’t possible with spreadsheets).

• Multi-dimensional modeling: Drivetrain’s software helps SaaS companies build complex multi-dimensional models, by tailoring inputs, calculations, and outputs as per their business requirements, all in a fraction of the time it would usually take on spreadsheets. You can get started quickly with built-in, customizable model templates. 

• Scenarios analysis: On Drivetrain’s robust platform, you can easily build and test multiple scenarios and perform what-if analysis to understand the impact of different scenarios (e.g., seasonality, market trends, etc.), on your financial forecasts and make the necessary adjustments immediately. 

• Version control and access: You don’t need to make multiple copies of your forecasting model anymore to ensure that you use the latest version to resume your calculations. On Drivetrain, you can just save it as a version, and restore it easily whenever you need to refer to it. find and restore them very easily. The role-based access feature also helps different users across teams to collaborate on the same model, in real time. This means that the version you work on will always be the latest, updated version.

‍Explore how Drivetrain empowers you to measure and track revenue from usage-based pricing models with ease.