Cash flow forecasting with usage-based pricing: Keys to unlock more effective planning

If traditional subscription-based forecasting is like sailing on predictable calm waters, forecasting with usage-based pricing is more like trying to keep your raft afloat in a choppy, unpredictable sea. A usage spike here, a seasonal dip there, a slip in the invoicing, and suddenly your carefully crafted financial model looks like it's about to sink. 

Of course, that’s probably not going to happen. You’ll get to work, tweaking your model to fit the complexities of your usage-based pricing. These and other complexities associated with usage-based pricing models underscore the importance of mastering them for the purposes of strategic planning and decision-making. For SaaS companies that rely on usage-based revenue, understanding how consumption can impact revenue and other aspects of the business can be the difference between being appropriately conservative or over-confident in your projections and spending. 

Accurate cash flow forecasting helps SaaS business leaders avoid cash flow shortfalls as well as identify and mitigate any cash-related challenges early on, make data-backed business decisions around hiring and expansion, plan for infrastructure development ahead of demand, and maintain a healthy cash runway for business operations. 

This article discusses the impact of usage-based pricing components on the process of cash flow forecasting in SaaS companies along with the challenges involved. It also explores practical approaches to forecast cash flows in a usage-based SaaS environment and the role of strategic finance software to improve the cash flow forecasting process. 

Understanding the usage-based pricing model

Usage-based pricing is deceivingly simple in concept— you pay for the product based on what you consume. Nothing more, nothing less. However, in practice, it can introduce a lot of complexity into your business that you’ll definitely want to think about if you’re considering implementing a usage-based pricing model in your business.  

The most common types of usage-based pricing models create a dynamic pricing structure that focuses on customer value:

• Per-unit usage pricing: Customers pay based on actual consumption of defined units (e.g., API calls, storage used). The relationship between usage and cost is linear—you pay more when you use more and vice versa. 
• Tiered pricing: In this model, customers pay a fixed price for a fixed allowance of units (e.g., API, storage, etc) and then pay overage fees for any additional usage.
• Volume pricing: This model incentivizes consumption (hence, volume). The higher the consumption, the lesser the fees. Customers are typically offered discounts if they purchase and consume more of your products or services.

One of the biggest differences between usage-based pricing and traditional subscription pricing lies in the value delivered. While it is easier to predict revenue in the subscription model, it does not really reflect the real value that was delivered to the customer. In usage-based pricing, the value customers are getting is more readily apparent as they are paying based on how much they use the product and use (or consumption) is intrinsically tied to value. After all, how many customers are going to waste their time using a product if it isn’t helping them? 

In recent years, hybrid pricing—a combination of fixed-rate (a committed monthly subscription fee) and one or more usage-based components—has gained a lot of traction among Saas businesses. Hybrid models give them more flexibility in the way they deliver value to (and charge) customers, while ensuring greater scalability of their product and services. 

However, given the inherent variability of usage-based or hybrid pricing models, calculating and tracking usage-based performance metrics can help SaaS finance teams come up with a predictable baseline revenue.

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How does usage-based pricing impact cash flow forecasting? 

Learning how to forecast revenue for usage-based pricing models is crucial for maintaining your SaaS business’ financial health and performance, whereas cash flow forecasting helps you predict the timing and amount of cash inflows, cash outflows, and projected cash balances.

A cash flow forecast is used as a planning tool to enable business leaders to analyze and make changes in spending to optimize their current cash reserves and improve cash flow when combined with spend analysis and budgeting. 

Traditional subscription-based SaaS cash flow forecasting is relatively straightforward. You need to project the amount of cash coming in from all sources and subtract your cash outflows, which include all your business and operating expenses. 

The cash coming into your business with a purely subscription-based model includes recurring revenue paid either upfront or monthly, and possibly one-time implementation fees and/or ongoing fees for customer support. 

Usage-based pricing complicates this as the recurring revenue depends on consumption patterns—which is variable. This is why forecasting with a usage-based pricing model is so complex.  

With usage-based pricing, you need to predict the usage and consumption pattern of each customer, seasonal factors, as well as usage trends and across customer segments. For example, if there’s a sudden surge in usage, you might have to revise your infrastructure growth plans to accommodate more usage and customers. Similarly, an unexpected decrease could impact your ability to fund planned growth initiatives and product development.

This variability creates unique challenges for SaaS CFOs and finance teams during financial planning. While subscription-based companies can plan headcount or infrastructure investments well in advance, companies with usage-based pricing  need more sophisticated forecasting models to track and manage cash flow effectively. 

The key difference between these pricing models lies in predictability versus growth potential. A traditional subscription-based model offers high predictability but limits the revenue for a given contract to the subscription amount. In contrast, while usage-based pricing is unpredictable, it does come with the ability to grow your revenue as customer usage increases. 

How to forecast cash flow with usage-based pricing

Cash flow forecasting with usage-based pricing involves estimating your future sales and expenses by:

• Forecasting income from usage: Start by analyzing historical usage patterns across your customer base. Then conduct a cohort analysis to identify trends by industry, company size, and seasonality. It is important to factor in both committed usage minimums and variable consumption patterns to establish baseline revenue expectations.
• Estimating cash inflows: Your sales pipeline must be studied to map expected usage patterns. You can do that by tagging opportunities in your CRM with usage scores. These scores, based on your history of similar customer profiles and industry benchmarks, will help predict initial usage levels. To make it more accurate, you could also consider payment terms and billing cycles to time cash inflows.
• Estimating cash outflows: You must calculate all infrastructure and variable costs that scale with customer usage, along with fixed operational expenses. This includes cloud hosting costs, customer support resources, and any third-party services that may vary with consumption. You also need to take into account any planned investments like team growth or technology investments for scaling the platform.
• Focusing on customer segmentation: You can improve the accuracy of your cash flow forecast by segmenting customers based on different factors, such as industry vertical, company size, and historical usage patterns. You could also consider creating separate forecasting models for each segment, as usage patterns often vary significantly across different customer types and use cases.
• Compiling the estimates into your forecast: You can combine your customer segment-specific projections along with pipeline-based predictions and committed minimum usage revenues to arrive at the most accurate cash flow forecast while using a usage-based pricing model. Further, you can conduct a scenario analysis to account for variability in usage patterns. You can also add in a few “what-if” scenarios to account for external factors that might affect customer consumption.
• Continuously reviewing and adjusting your estimated cash flows against the actual: Lastly, it is important to compare your actual data versus the forecasted usage patterns, tracking accuracy by customer or industry segment and documenting significant variations. Use these insights to continuously refine your forecasting models and adjust assumptions based on emerging patterns and market conditions.

Challenges in cash flow forecasting with usage-based pricing

While cash flow forecasting for SaaS businesses can be challenging on its own, the process is further augmented by the unpredictability of the usage-based components. Some of the unique challenges are discussed below.

Revenue forecasting lacks predictability

Seasonal fluctuations, unexpected usage spikes, and varying consumption patterns make revenue forecasting more challenging. Unlike subscription models with fixed monthly fees, usage-based revenue lacks guaranteed minimums (unless specifically contracted). Even when customers purchase prepaid units, uncertain consumption timing affects revenue recognition and cash flow timing.

Let’s say a company had projected increased product usage by more customers during a certain period and had invested in resources and infrastructure accordingly. However, the actual demand and usage during the season fell short of the projection, resulting in more expenses (cash outflow). 

Conversely, instead of anticipating the demands and usage, the company was more conservative in their estimates. Therefore, during the season, due to lack of resources, they could not keep up with the demand, missing out on new customers and cash inflow opportunities. 

This is a classic example of the sheer unpredictability of the usage-based pricing model when it comes to revenue forecasting.

Capacity planning becomes a balancing act

Without predictable usage patterns, finding the right balance between capacity and cost efficiency can become complex. Over-provisioning can lead to higher fixed costs and lower gross margins, while under-provisioning could result in not being able to provide adequate service and missed revenue opportunities (not to mention customer satisfaction).

Invoicing in arrears creates cash flow gaps

One of the most fundamental challenges of usage-based pricing is the timing mismatch in cash flows as the invoice is raised after a customer’s consumption period. However, as a SaaS business, you have to pay for infrastructure and operational costs upfront. This means the revenue collection might lag by 30-60 days. This gap can strain working capital, especially when your vendors require advance payments or during rapid growth phases.

Strategic finance software helps simplify cash flow forecasting with usage-based pricing models 

While the usage-based pricing model is beneficial for both customers (in terms of the value delivered) and service providers (in terms of aligning value with cost, attracting a diverse customer base, and maximizing revenue options), the sheer unpredictability of this pricing model does make the cash flow forecasting process more complex for SaaS companies. The challenges range from invoicing delays to capacity planning to budgeting to revenue unpredictability. Therefore, cash flow forecasting and financial planning, in such a situation, demands a more robust and sophisticated approach beyond using unwieldy spreadsheets. 

Modern cashflow forecasting software helps bridge these gaps by automating data collection across systems, providing real-time visibility into customer consumption trends, segmenting customers based on industry type or usage patterns, modeling different scenarios, and adjusting estimates in the forecasts—thereby enabling finance teams to develop more accurate cash flow and revenue projections. 

For companies transitioning to or operating with usage-based pricing, financial forecasting software has become essential for maintaining healthy cash flows and planning for growth. 

Drivetrain, a robust, third-generation Saas FP&A solution, specifically helps address these unique challenges in cash flow forecasting (caused by the usage-based components) by:

• Automating data collection and analysis regarding customer usage patterns
• Enabling granular customer segmentation and cohort analysis
• Offering real-time variance analysis and forecast adjustments
• Providing AI-powered forecasting models that learn from historical patterns
• Performing scenario modeling and “what-if” analysis

Learn more about how Drivetrain can help you enhance your cash flow forecasting process while taking into account your SaaS business’ unique usage-based pricing model.