How to calculate and project your SaaS company’s unit economics to boost profitability

In the movie Moneyball, Brad Pitt’s character Billy Beane employs sabermetrics (sports data analytics) to assemble a competitive baseball team on a limited budget. Broadly, sabermetrics is used to compare one player's performance against others, predict future performance, and understand a player's contribution to the team as a whole. If this were a movie about SaaS, Billy Beane would be a startup founder or CFO using unit economics to maximize profitability from customer acquisition and retention while keeping a firm handle on expenses. 

The basic idea behind unit economics is that it provides a very fine-grained way to look at profitability, evaluating it at the level of a single unit sold, taking into account the cost  incurred by the business to sell that unit. In the SaaS context, this type of analysis provides powerful insights for driving growth in your business. 

This article discusses unit economics in SaaS, why it matters, and provides detailed steps for calculating it. You’ll also learn how to project your unit economics over a three-year period to inform your strategic planning.

What is SaaS unit economics?

SaaS CFOs and finance teams routinely develop financial forecasts (cash flow, budget, etc.) to analyze and track business performance and financial health. While projections provide a comprehensive, data-backed view of the business, they don't necessarily tell the whole story. This is where you need unit economics, which allows you to look at your business at a deeper level to ensure that you’re growing in the right direction.

An important question for every startup founder to ask is, “How much profit do we make with each new customer?”  

Unit economics will answer that question because it measures the profitability of a business on a per-unit basis. For SaaS businesses, unit economics essentially refers to the profit and loss (P&L) associated with a single customer. 

Unit economics enables early-stage startup leaders to track their total revenue and net numbers in a more detailed way to gain a deeper understanding of how their total business costs and growth initiatives are driving results and make more insightful projections around revenue and gross margins.

To understand unit economics, let’s first look at what constitutes a “unit” in SaaS. 

SaaS companies typically follow the “units-as-customers” model wherein each customer/business is one unit, irrespective of the number of subscriptions they buy. 

Note that you could define your “unit” in a more granular way if you wanted to. Let’s say your customer requires more effort and spend per subscription/account to get started. In such a situation, those expenses are monitored and tracked as separate units (based on agreed upon categorizations). 

Conversely, if the client business simply adds and removes users per their requirements, then there would be no changes to your customer acquisition costs (CAC), in which case the entire business could be counted as a single unit. 

In either case, unit economics is key to understanding how much it costs to acquire a customer vs. what you earn from them.

Importance of unit economics for SaaS businesses

Tracking and analyzing unit economics helps business leaders identify any gaps in projections, optimize expenses, and ultimately increase profits, by:

• Predicting business growth: Unit economics are a highly reliable indicator of your company’s long-term financial health. If you know how much profit you make from each new customer, you can determine the number of customers required to cover the company’s expenses and reach the break-even point. This helps with more effective cash flow planning and resource allocation for business growth. 

• Making data-backed business decisions: A thorough understanding of the cost and revenue per unit enables SaaS business leaders to make more informed decisions around cost drivers and identify areas where improvement is needed to maintain or grow profit margins. It is also quite useful in evaluating the effectiveness of marketing strategies and budget. 

• Adjusting pricing strategies: You can also use unit economics to determine the optimal pricing strategy for products/services and adjust pricing tiers. For example, you may decide to move features that cost more to provide to a higher tier plan to boost profitability. Monitoring your unit economics is particularly useful for informing usage-based pricing strategies, allowing you to fine-tune your pricing to  accommodate and optimize for variable usage among different customer segments.

• Attracting investors: Investors look for evidence that each unit/customer contributes positively to the bottom line. Positive unit economics helps to assure investors that the business model and/or product is viable and the company is a worthwhile investment. 

How to calculate the current unit economics of your SaaS business 

The key thing to remember about unit economics is that it’s designed to answer the question, how much value does one customer, on average, generate for the business? It's another way to understand your company's profitability at a more granular level than your P&L can show.

You can use the steps below to calculate the unit economics at an average per-customer level for your business overall, or for different cohorts, such as customers in a specific region or market segment. The steps discussed below work for both. 

Step 1: Calculate the per-customer revenue

To determine this, you'll sum all sources of revenue associated with your customer base or cohort and then determine the relative contribution of each type of revenue (subscription-based revenue vs. other sources) to the total.  

For subscription revenue, you can use the average revenue per account (ARPA) calculation wherein you divide the total annual recurring revenue (ARR) of your business in a given period by the number of customers in that same period: 

For example, let’s say your ARR is $100,000 and you have 10 customers:

Additional sources of revenue would include non-recurring revenue such as implementation fees and professional services revenue. As with ARPA, you would use the average of these revenue types, calculating it in the same manner to get your per-customer value.   

Step 2: Calculate direct costs

The next step is to calculate the direct costs and a gross margin on a per-customer level (Step 3).

In SaaS, the cost of goods sold (COGS) include the direct costs of creating and delivering the product/service. For our example, COGS would include software hosting, implementation costs, and customer support costs (payroll costs of the client services manager). The CSM’s payroll costs should ideally be allocated against the different types of work and their associated revenue streams, such as:

• Costs related to the ARR your customers are generating for the business, which typically include onboarding costs (implementation) and ongoing support costs.
• Costs related to professional services provide additional revenue and are accounted for separately from those related to ARR when calculating unit economics. 

You’ll calculate each of the direct costs included in your COGS as an average, per-customer cost by summing each type of direct cost and dividing the result by your total number of customers.   

Step 3: Calculate the contribution margin

This is where we calculate the average gross margin each customer contributes to the business. In terms of unit economics, this is referred to as the "contribution margin" (i.e., amount of profit) of a single customer. 

To calculate the contribution margin, you’ll consider all the revenue sources, including recurring revenue (ARPA) and the average non-recurring revenue per customer that you calculated in Step 1, which would include any revenue associated with onboarding and professional services. 

You can use the equation below to calculate contribution margin. Note that while ARPA typically includes only non-recurring revenue, in the formula below it reflects all sources of revenue.  

Step 4: Calculate the other per-customer costs 

This step determines other customer acquisition costs (one-time spend) associated with sales and marketing (S&M). These costs will be determined using a per-customer average.

There are three main types of costs in sales and marketing: 

• Inbound marketing costs include content marketing, search engine optimization, digital and social media marketing, and marketing automation tools. 
• Outbound marketing costs include cold outreach, paid advertising, events and webinars, etc. 
• Sales costs are comparatively easier to calculate since these include the commissions and salaries of the sales team, as well as the salaries of business development representatives for outbound sales. 

Step 5: Calculate the net value per customer

Now that we have the contributions from the different revenue streams and the S&M spend, it is time to calculate the net value per customer.

The amount of value that each customer generates for your business can be determined by subtracting the average S&M spend per customer from the total contribution, which is by definition, a per-customer value. 

How to project your unit economics over time

The steps and calculations above give you your unit economics for one year, which answers the basic question of how much profit your company currently makes from a single customer. But, why stop there?

Taking the results from your calculation above as Year 1, you can use the same process to extrapolate for Years 2 and 3 to estimate the cumulative net value per customer would generate for your business over three years (or any time frame per your requirements). Let’s see how! 

Step 6. Project your ARPA for Year 2 and Year 3

You need to first project your ARPA for Year 2 and Year 3 using net revenue retention (NRR). 

Let’s look at an example. At the start of Year 1 (12 months), you had 10 customers that were generating $100,000 of ARR. At the end of the year, in the 13th month, the NRR would show the percentage of revenue retained from your existing customer base. That is, has your $100,000 of ARR become 90% NRR ($90,000) or 110% NRR ($110,000)?  

Now, to calculate your Year 2 ARPA, you need to first determine your Year 1 NRR. To do so, you need to use the average NRR for all customers, which can be calculated by taking the last 12-months’ data for each individual customer and then averaging it. 

Then you need to multiply the Year 1 NRR by the Year 1 ARPA.

Do note that, for this example, you can use Year 1 NRR to extrapolate for both Years 2 and 3. However, if you have customers that have been active for three years, you can use the actuals to project NRR for Year 3 based on 26 months’ worth of data.  

Step 7. Calculate contributions for Year 2 and Year 3

Now that you have the full numbers for Year 1 and the ARPA for Year 2 and Year 3, you need to build in the direct costs for Years 2 and 3. To calculate these, you will use the same process as you did to calculate them for Year 1 (Step 2), except now they will be based on projections. 

• Hosting costs will be based on projections (a per-customer average of your projected number).
• Support costs are also based on projections. It is important to note here that implementation and onboarding costs will not be considered in Years 2 and 3 since these are one-time costs. Only ongoing support costs are taken into account. 
• S&M costs are also regarded as a one-time spend for customer acquisition, so they will not be considered in Years 2 and 3. 

Step 8. Project the cumulative net value of the customer 

Now that we have the contributions for Years 2 and 3, we can determine our unit economics over three years—by taking the sum of Year 1 net value (since these include S&M and implementation costs), Year 2 contribution, and Year 3 contribution. 

Usually, the unit economics for Year 1 would be lower since there would be higher sales and marketing spend as part of your customer acquisition costs along with implementation costs. However, for Years 2 and 3, while you’re generating revenue and even increasing direct costs (such as, hosting and ongoing support), you’re not spending any more on sales and marketing or implementation. 

These projections not only provide a big picture view of your SaaS business regarding your revenue and expenses at a per-customer level but also reveal useful insights in terms of the costs of acquiring and retaining a customer and the value derived from them. 

Further, a thorough understanding of the unit economics of each customer or type of customer gives SaaS business leaders more information into what seems to be working best for their business, such as outbound vs. inbound strategies, region, market segment, etc., to determine which of these factors generate the greatest value per customer.

How Drivetrain makes calculating and understanding your unit economics easier

Taking a unit economics approach towards business helps SaaS leaders get a better understanding of the profitability of their business model along with the financial health and performance of their company as it grows. 

It is important to track and analyze other key SaaS metrics that can impact your unit economics, such as CAC, LTV, churn rate, logo retention rate, etc., to better understand the efficiency of your business in terms of the value generated from a customer. 

Doing so requires really granular analysis and complex calculations which can be challenging and time-consuming using only spreadsheets. Any slight mistake in data entry, formulas, or calculations can lead to significant discrepancies and inaccuracies in your projections and models, impacting strategic decision-making and business performance. Neither do they encourage collaboration across different users and teams. Depending on the size of your financial model, spreadsheets can also become unwieldy and inefficient. 

This is where Drivetrain, a purpose-built financial planning and analysis (FP&A) software comes in. In addition to automating data aggregation from all your source systems, the platform’s powerful features enable you to easily calculate your NRR, ARR, and other financial and SaaS metrics in real time and use them to build the models you need to understand your business at a deeper level. These include: 

• Native integrations and data consolidation: With over 200 integrations, Drivetrain automates data consolidation across disparate systems, including ERPs, HRIS, CRMs, and billing apps, and allows you to slice and dice that data per your business requirements to generate insights in real time.
• Predictive forecasting: On Drivetrain’s user-friendly platform, you can easily start creating forecasting models with the help of different types of built-in forecasting methods, access historical data whenever you need it, revise assumptions in your forecasts as needed, even conduct scenario analysis to arrive at more accurate projections—without jumping across different spreadsheets.
• Multi-dimensional modeling: You can also build and analyze complex financial models across multiple dimensions, including region, market segment, product, channel, etc., make manual adjustments, customize calculations, and test different scenarios, all on the same platform. Drivetrain's familiar, spreadsheet-like and intuitive user interface with built-in plain English formulas ensures that even non-finance users can quickly build multi-dimensional models. 
• Dynamic dashboards: Interactive dashboards help monitor key financial metrics and performance indicators, identify trends, as well as visualize and communicate business performance and financial health in a format that is easily understood by all your stakeholders
• Collaboration with access control: Collaborating across departments or with multiple users on financial models and forecasts is much easier with Drivetrain. All users can work on the same "model" (the latest updated version). Further, the role-based access control feature ensures that any sensitive financial data is protected and users get access to only the data they need to perform their roles efficiently. 

Powerful yet simple to use, Drivetrain has the full range of FP&A features that SaaS business leaders and finance teams require to better understand their business’ financial performance and make more accurate projections.