Stripe contains some of the most important data a SaaS company needs to understand and forecast recurring revenue, including subscriptions, customers, pricing, cancellations, upgrades, downgrades, and recurring payments.
But looking at historical Stripe metrics is different from forecasting what happens next.
A SaaS revenue forecast uses historical subscription performance and assumptions about future subscriber growth, churn, expansion, contraction, and pricing to estimate future recurring revenue. When Stripe subscription data is combined with accounting data from QuickBooks Online, SaaS companies can go a step further and see how changes in recurring revenue could affect profitability, cash flow, and runway.
RunSmart by Projection Genie connects to both Stripe and QuickBooks Online to automatically establish a financial baseline from historical business performance and allows SaaS founders to model how changes in key subscription drivers could affect the company's financial future.
This guide explains how SaaS revenue forecasting works, which Stripe metrics matter, how the calculations fit together, and how SaaS founders can use those forecasts for financial planning.
What Is SaaS Revenue Forecasting?
SaaS revenue forecasting is the process of estimating future revenue based on recurring subscription revenue, expected customer growth, churn, expansion, contraction, pricing, and other factors that affect the amount of revenue generated by customers over time.
Unlike a traditional sales forecast based primarily on expected sales, a SaaS revenue forecast needs to account for the recurring nature of subscription revenue.
A simplified SaaS revenue forecast can be expressed as:
Ending MRR = Beginning MRR + New MRR + Expansion MRR - Contraction MRR - Churned MRR
Where:
- Beginning MRR is monthly recurring revenue at the beginning of the period.
- New MRR is recurring revenue added from new customers.
- Expansion MRR is additional recurring revenue from existing customers through upgrades, additional seats, usage, or other expansion.
- Contraction MRR is recurring revenue lost when existing customers downgrade or reduce spending.
- Churned MRR is recurring revenue lost from customers who cancel.
This creates a recurring revenue baseline that can then be projected into future periods.
Can Stripe Data Be Used to Forecast SaaS Revenue?
Yes. Stripe Billing data can provide much of the historical subscription information needed to understand the recurring revenue behavior of a SaaS business.
Depending on how a company uses Stripe, relevant data can include:
- Active subscriptions
- New subscriptions
- Canceled subscriptions
- Subscription prices
- Recurring payments
- Customer upgrades and downgrades
- Monthly recurring revenue
- Customer growth
- Churn
- Expansion and contraction activity
Historical Stripe data helps establish how the subscription business has actually behaved.
Forecasting then takes that historical baseline and projects what could happen in the future.
This distinction is important: Stripe data describes subscription activity, while a financial forecast estimates where that activity may lead.
Which SaaS Metrics Matter Most for Revenue Forecasting?
Several subscription metrics have an especially large impact on a SaaS revenue forecast.
These metrics interact with one another, which is why looking at a single SaaS KPI in isolation can provide an incomplete picture of future revenue.
How Do You Calculate MRR?
Monthly Recurring Revenue, or MRR, represents the recurring subscription revenue associated with a SaaS company's active customers for a month.
For a simple SaaS business where every customer pays the same amount:
MRR = Number of Active Customers × Monthly Subscription Price
For example, suppose a SaaS company has 500 customers paying an average of $100 per month.
MRR = 500 × $100 = $50,000
The company's current MRR would therefore be $50,000.
For businesses with multiple plans, upgrades, discounts, or usage-based components, MRR calculations become more complex because recurring revenue needs to be normalized across customers and billing intervals.
How Do You Calculate ARR?
Annual Recurring Revenue, or ARR, is commonly used to annualize recurring subscription revenue.
A simplified calculation is:
ARR = MRR × 12
If a SaaS company has $50,000 in MRR:
ARR = $50,000 × 12 = $600,000
ARR should not be confused with total annual revenue. ARR represents annualized recurring revenue and generally does not include non-recurring revenue.
How Does Customer Churn Affect a SaaS Revenue Forecast?
Customer churn measures the percentage of customers lost during a period.
A simplified customer churn calculation is:
Customer Churn Rate = Customers Lost During Period ÷ Customers at Beginning of Period × 100
Suppose a SaaS company begins the month with 500 customers and 15 customers cancel.
Customer Churn Rate = 15 ÷ 500 × 100 = 3%
If no new customers were added, the company would finish with 485 customers.
Churn becomes particularly important when forecasting multiple months because its effects compound.
A higher churn rate doesn't just reduce revenue in the month a customer cancels. It also removes the recurring revenue that customer otherwise could have generated in subsequent months.
How Do You Forecast SaaS Revenue?
A SaaS revenue forecast can be built by projecting the major drivers of recurring revenue for each future period.
Consider a simplified SaaS company with:
- 500 beginning customers
- $100 average monthly revenue per customer
- 25 new customers per month
- 3% monthly customer churn
- No expansion or contraction revenue
The company begins with:
500 customers × $100 = $50,000 MRR
At a 3% monthly churn rate:
500 × 3% = 15 customers lost
If the company also adds 25 new customers:
Ending Customers = 500 + 25 - 15 = 510
At an average $100 per customer:
Projected Ending MRR = 510 × $100 = $51,000
The same calculation can then be repeated for subsequent periods using the previous month's ending customer count as the next month's starting point.
This creates a forward-looking subscription revenue forecast.
Why Historical Performance Matters
Forecast assumptions shouldn't exist in a vacuum.
If a SaaS company has historically added 20 to 30 customers per month, experienced churn between 2% and 4%, and generated expansion revenue from approximately 10% of its customers, those patterns provide useful context for establishing a baseline forecast.
A forecast can then answer two different questions:
What is likely to happen if current patterns continue?
and:
What could happen if those patterns change?
The second question is where scenario modeling becomes especially useful.
How Do You Model SaaS Revenue Scenarios?
Scenario modeling allows SaaS founders to change individual business assumptions and measure how those changes could affect future performance.
For example, assume a company currently has:
- $100,000 MRR
- 3% monthly churn
- 5% monthly subscriber growth
Management is considering several initiatives designed to reduce churn.
Instead of assuming those initiatives will work, the company could model multiple possibilities:
Each scenario produces a different future customer base and recurring revenue trajectory.
The differences become increasingly significant over longer forecast periods because both customer growth and churn compound over time.
Why Isn't Stripe Data Alone Enough for a Complete Financial Forecast?
Stripe provides valuable information about customers, subscriptions, billing, and recurring revenue.
But SaaS founders usually need to understand more than future revenue.
They also need to know what that revenue could mean for:
- Operating expenses
- Payroll and hiring costs
- Profitability
- Cash flow
- Debt obligations
- Assets and liabilities
- Working capital
- Capital requirements
- Cash runway
Much of that information lives in the company's accounting system rather than its subscription billing platform.
That's why combining Stripe with QuickBooks Online creates a more complete foundation for SaaS financial planning.
Stripe can help explain what is happening with the subscription engine, while QuickBooks provides the broader financial picture.
Stripe vs. QuickBooks for SaaS Financial Planning
Stripe and QuickBooks serve different purposes, and neither needs to replace the other.
For SaaS financial forecasting, the value comes from connecting the operational subscription data with the financial accounting data.
How RunSmart Uses Stripe and QuickBooks for SaaS Forecasting
RunSmart by Projection Genie combines Stripe subscription data with QuickBooks Online financial data to give SaaS founders a forward-looking view of their business without requiring them to build and maintain a complex financial model.
RunSmart automatically analyzes historical performance to establish a baseline forecast based on the company's actual data.
Founders can then model changes to key SaaS drivers such as:
- Subscriber growth
- Churn
- Expansion revenue
- Pricing
Those revenue assumptions can be modeled alongside broader business decisions involving hiring, operating expenses, financing, and other financial changes.
This allows a founder to see how a SaaS decision could flow through the broader financial picture.
For example:
What happens if monthly churn increases from 3% to 5%?
The immediate effect is fewer retained subscribers and lower recurring revenue.
But the more important financial questions may be:
How does that affect revenue over the next 12 months?
What happens to profitability?
How does it change projected cash flow?
Does it shorten the company's runway?
RunSmart connects those questions by combining subscription performance with the company's broader financial data.
Example: Modeling the Financial Impact of Higher Churn
Consider a SaaS company generating $100,000 in MRR.
Management's baseline assumes monthly churn will remain around 3%, but the founder wants to understand what happens if churn increases to 5%.
The company can create a scenario using the higher churn assumption while keeping other assumptions unchanged.
RunSmart can then recalculate the projected subscription performance and incorporate the resulting revenue changes into the company's broader financial forecast.
Instead of simply seeing:
“MRR will be lower.”
The founder can evaluate how the change affects projected:
- Revenue
- Profitability
- Cash flow
- Financial health
- Runway
That distinction turns SaaS metrics into financial planning information.
SaaS Analytics vs. SaaS Financial Forecasting
SaaS analytics and financial forecasting answer related but different questions.
SaaS analytics primarily tells you what has happened and what is happening.
For example:
- What is our current MRR?
- What was churn last month?
- How many subscribers did we add?
- What is our net revenue retention?
Financial forecasting asks what could happen next.
For example:
- Where is revenue headed if current performance continues?
- What happens if churn increases?
- What happens if subscriber growth accelerates?
- How would a pricing change affect revenue?
- Can we afford additional hires?
- When could we become profitable?
- How would these decisions affect cash runway?
SaaS companies need both.
Historical analytics establishes the evidence. Forecasting uses that evidence to help evaluate the future.
Frequently Asked Questions
Can Stripe be used for financial forecasting?
Stripe data can be an important input into a SaaS financial forecast because it contains information about subscriptions, customers, recurring billing, cancellations, and other revenue activity. A complete company-level financial forecast generally requires additional financial data, such as expenses, assets, liabilities, debt, and cash flow.
Can Stripe data be combined with QuickBooks for forecasting?
Yes. Combining Stripe subscription data with QuickBooks Online accounting data allows SaaS companies to connect recurring revenue behavior with their broader financial performance. RunSmart combines these data sources to create forward-looking financial forecasts and model SaaS business scenarios.
What is the difference between MRR and revenue?
MRR represents normalized monthly recurring subscription revenue. Accounting revenue represents revenue recognized according to applicable accounting practices and can include recurring and non-recurring sources. The two should not automatically be treated as interchangeable.
What is the difference between MRR and ARR?
MRR expresses recurring revenue on a monthly basis. ARR expresses recurring revenue on an annualized basis. A common simplified calculation is ARR = MRR × 12, although SaaS businesses with complex contracts may require more nuanced calculations.
What is the most important metric for forecasting SaaS revenue?
There is no single metric that produces a complete SaaS revenue forecast. Beginning recurring revenue, new customer growth, churn, expansion, contraction, and pricing can all materially affect future revenue.
Does lower churn increase future SaaS revenue?
All else being equal, lower churn results in more customers and recurring revenue being retained. Because SaaS revenue recurs, the financial effect can compound over time.
Why combine Stripe and QuickBooks?
Stripe provides detailed subscription and billing information, while QuickBooks provides accounting information such as expenses, assets, liabilities, debt, and cash flow. Combining the two provides a more complete view of both the SaaS revenue engine and the company's overall financial position.
Can RunSmart model changes in SaaS churn?
Yes. RunSmart allows SaaS founders to model changes to churn and see how different assumptions could affect future revenue and the broader financial forecast.
Can RunSmart model SaaS pricing changes?
Yes. SaaS founders can model changes to pricing to evaluate how different pricing assumptions could affect projected financial performance.
Can RunSmart forecast cash flow and runway from SaaS data?
RunSmart combines SaaS subscription data with the company's QuickBooks financial data so changes in revenue assumptions can be evaluated alongside expenses and other financial activity. This allows founders to evaluate potential effects on future cash flow, profitability, and runway.
Turning Stripe Data Into a Forward-Looking Financial Plan
Stripe gives SaaS founders detailed visibility into the engine generating their recurring revenue.
But understanding today's MRR, churn, and subscriber count is only part of financial planning.
Founders also need to understand where those metrics could take the company and how changes in growth, churn, expansion, and pricing could affect revenue, profitability, cash flow, and runway.
By combining Stripe subscription data with QuickBooks Online financial data, RunSmart turns historical business performance into a forward-looking financial baseline and lets SaaS founders model how the decisions they're considering could change their financial future.
Instead of maintaining a complex financial model manually, founders can start with what their business has actually done and focus on the more important question:
What happens if the future is different from the past?
