MRR and ARR are two of the most widely used metrics in SaaS, but historical MRR and ARR only tell you where recurring revenue stands today.
Forecasting asks a different question:
Where could MRR and ARR be in the future?
A useful SaaS recurring revenue forecast starts with the company's existing subscription base and models how future customer growth, churn, expansion, contraction, and pricing could change that base over time.
Stripe subscription data can provide much of the historical information needed to understand those recurring revenue drivers.
RunSmart by Projection Genie connects Stripe and QuickBooks Online data to automatically establish a forward-looking financial baseline and allows SaaS founders to model how changes in subscriber growth, churn, expansion revenue, and pricing could affect future MRR, ARR, profitability, cash flow, and runway.
This guide explains how MRR and ARR are calculated, which Stripe subscription metrics matter most, and how to turn historical recurring revenue data into a forward-looking SaaS forecast.
What Is MRR?
Monthly Recurring Revenue, or MRR, represents the normalized recurring subscription revenue a SaaS company generates in a month.
A simple MRR formula is:
MRR = Active Subscribers × Average Monthly Recurring Revenue per Subscriber
For example, if a SaaS company has 500 subscribers paying an average of $100 per month:
500 × $100 = $50,000 MRR
In practice, SaaS companies may have multiple subscription plans, discounts, annual contracts, upgrades, downgrades, and usage-based components, so MRR calculations can be more complex.
The purpose of MRR is to normalize recurring subscription revenue into a monthly measure that can be tracked consistently over time.
What Is ARR?
Annual Recurring Revenue, or ARR, represents recurring subscription revenue on an annualized basis.
For a simple monthly subscription business:
ARR = MRR × 12
If a company has $50,000 in MRR:
$50,000 × 12 = $600,000 ARR
ARR is useful for expressing the recurring revenue base in annual terms.
However, ARR should not automatically be treated as the same thing as total annual accounting revenue.
A company may also generate implementation fees, consulting revenue, usage charges, or other non-recurring revenue that falls outside its core recurring revenue base.
What Is the Difference Between MRR and ARR?
MRR and ARR measure the same recurring revenue concept over different time horizons.
For monthly operating analysis and forecasting, MRR is often the more useful metric because changes in growth, churn, expansion, and contraction happen month by month.
ARR provides a convenient annualized view of that recurring revenue.
Can Stripe Data Be Used to Forecast MRR and ARR?
Yes. Stripe subscription and billing data can provide historical information about the factors that cause recurring revenue to increase or decrease.
Those factors can include:
- Active subscriptions
- New subscriptions
- Cancellations
- Subscription pricing
- Upgrades
- Downgrades
- Recurring payments
- New MRR
- Churned MRR
- Expansion MRR
- Contraction MRR
Historical Stripe data can therefore help establish how the recurring revenue engine has behaved.
Forecasting then extends those historical patterns into future periods and allows founders to test what could happen if those patterns change.
What Drives MRR Growth?
MRR changes because recurring revenue is being added or lost.
A common recurring revenue formula is:
Ending MRR = Beginning MRR + New MRR + Expansion MRR - Contraction MRR - Churned MRR
Each component represents a different business event.
Understanding these components is important because two companies can produce the same MRR growth rate for very different reasons.
One may be growing through new customer acquisition.
Another may be generating most of its growth through expansion from existing customers.
Those businesses may have very different future financial profiles.
How Do You Forecast MRR?
A simple MRR forecast starts with beginning recurring revenue and estimates the additions and losses expected during each future period.
Suppose a SaaS company begins the month with:
- $100,000 beginning MRR
- $10,000 expected new MRR
- $4,000 expected expansion MRR
- $2,000 expected contraction MRR
- $5,000 expected churned MRR
Projected ending MRR is:
$100,000 + $10,000 + $4,000 - $2,000 - $5,000 = $107,000
That $107,000 then becomes the starting recurring revenue base for the next month.
Repeating this process across future periods creates an MRR forecast.
How Do You Forecast ARR?
ARR can be derived from forecast MRR when the business model supports that simplified relationship.
If projected MRR is $107,000:
Projected ARR = $107,000 × 12
Projected ARR = $1,284,000
If projected MRR grows to $125,000 six months later:
$125,000 × 12 = $1,500,000 ARR
This gives founders a future annualized recurring revenue view based on the forecasted monthly subscription base.
How Do You Forecast MRR Using Subscriber Growth?
MRR can also be forecast from projected subscriber counts.
A simplified customer model is:
Ending Subscribers = Beginning Subscribers + New Subscribers - Churned Subscribers
Projected MRR can then be estimated as:
Projected MRR = Ending Subscribers × Average Monthly Recurring Revenue per Subscriber
Suppose a company begins with:
- 1,000 subscribers
- $100 average monthly recurring revenue per subscriber
- 60 new subscribers
- 30 churned subscribers
Ending subscribers:
1,000 + 60 - 30 = 1,030
Projected MRR:
1,030 × $100 = $103,000
This approach is especially useful when subscriber growth and customer churn are major drivers of the forecast.
How Does Churn Affect MRR and ARR Forecasts?
Churn reduces the recurring revenue base.
If a customer cancels, the company loses not only the current month's recurring revenue but also the future recurring revenue that customer may otherwise have generated.
Suppose a SaaS company has:
- $100,000 beginning MRR
- 3% monthly revenue churn
A simplified monthly churn amount would be:
$100,000 × 3% = $3,000 churned MRR
If churn increases to 5%:
$100,000 × 5% = $5,000 churned MRR
That represents an additional $2,000 of recurring revenue lost in the first month.
Because each month's ending MRR becomes the next month's starting point, the effect can compound over time.
How Does Expansion Revenue Affect MRR Forecasting?
Expansion revenue increases recurring revenue from customers the company already has.
Expansion can come from:
- Plan upgrades
- Additional seats
- Increased usage
- Additional recurring products
- Higher contract values
Suppose a company begins with $100,000 in MRR and generates $6,000 in expansion MRR.
Without considering other changes:
$100,000 + $6,000 = $106,000 MRR
Expansion is especially important because it allows recurring revenue to grow without relying entirely on new customer acquisition.
How Does Contraction Affect MRR?
Contraction occurs when an existing customer continues subscribing but pays less.
Examples include:
- Downgrading to a lower-priced plan
- Removing seats
- Reducing usage
- Moving to a smaller contract
Suppose a company loses $3,000 of MRR through contraction.
That amount reduces ending MRR even though those customers have not fully churned.
This is why a SaaS forecast should distinguish between:
- Customer churn
- Revenue churn
- Contraction
- Full cancellations
Each affects recurring revenue differently.
How Do Pricing Changes Affect MRR and ARR?
Pricing changes can alter recurring revenue even when the number of customers remains unchanged.
Suppose a SaaS company has 1,000 subscribers paying an average of $100 per month.
Current MRR:
1,000 × $100 = $100,000
Current ARR:
$100,000 × 12 = $1,200,000
If average monthly pricing rises to $110:
1,000 × $110 = $110,000 MRR
Projected ARR:
$110,000 × 12 = $1,320,000
That represents a potential increase of:
$120,000 in annualized recurring revenue
However, a realistic pricing scenario may also consider whether higher prices affect churn, upgrades, downgrades, or customer acquisition.
Why Is Historical MRR Growth Not Enough for a Forecast?
A forecast based only on historical MRR growth can hide what is actually driving the change.
Suppose MRR grew 8% last month.
That growth could have resulted from:
- Strong new customer acquisition
- Lower churn
- Higher expansion revenue
- A pricing increase
- A temporary reduction in contraction
Those drivers may not continue at the same rates.
A stronger forecast separates the individual components of MRR so founders can understand which assumptions are responsible for future growth.
How Do You Build a Baseline MRR Forecast?
A baseline MRR forecast represents where recurring revenue appears to be heading based on historical performance before additional what-if assumptions are introduced.
For example, historical data may indicate:
- 5% monthly new subscriber growth
- 3% monthly customer churn
- 2% monthly expansion
- 1% monthly contraction
Those historical patterns can be used to establish an initial forward-looking baseline.
The founder can then model alternative assumptions.
This separates two questions:
Where is MRR heading if current patterns continue?
and:
What could MRR look like if growth, churn, expansion, or pricing changes?
How Do You Model MRR Scenarios?
MRR scenarios allow founders to compare different assumptions about the recurring revenue engine.
For example:
Each scenario produces a different MRR trajectory.
The resulting forecast can then be translated into ARR and incorporated into the broader company financial forecast.
Example: Forecasting MRR Over 12 Months
Suppose a SaaS company starts with:
- $100,000 MRR
- $8,000 monthly new MRR
- 2% monthly expansion
- 1% monthly contraction
- 3% monthly revenue churn
The exact result will depend on how each driver is applied over time, but the core process is repeated monthly:
Beginning MRR
+ New MRR
+ Expansion MRR
- Contraction MRR
- Churned MRR
= Ending MRR
The ending MRR from Month 1 becomes the beginning MRR for Month 2.
Repeating the calculation through Month 12 creates the annual forecast trajectory.
The important point is that recurring revenue compounds from one period to the next.
Should MRR Forecasts Use Customer Churn or Revenue Churn?
It depends on how the forecast is constructed.
If the forecast begins with customer counts, customer churn is especially useful.
If it begins directly with recurring revenue, revenue churn may provide a more direct financial measure.
For businesses with customers paying substantially different prices, using revenue-based measures can help capture the financial importance of larger customer losses.
How Do MRR and ARR Connect to Cash Flow?
MRR and ARR are recurring revenue metrics, not cash flow metrics.
A company can grow MRR while cash flow deteriorates.
For example, MRR may rise while the company also:
- Hires aggressively
- Increases marketing spending
- Invests in product development
- Makes debt payments
- Pays annual expenses
- Experiences timing differences between billing and cash collection
That is why MRR and ARR forecasts should eventually be connected to a broader financial forecast.
Stripe helps explain recurring revenue behavior.
QuickBooks provides the broader accounting and cash flow context.
Why Isn't ARR the Same as Cash?
ARR represents annualized recurring revenue.
It does not represent the amount of cash currently available to the business.
For example, a company might have:
- $1.2 million ARR
- $200,000 cash
- $80,000 monthly cash burn
The ARR figure alone does not indicate how long the company can continue operating.
That requires understanding actual cash balances and projected cash inflows and outflows.
Why Isn't MRR the Same as Accounting Revenue?
MRR is a SaaS operating metric designed to normalize recurring subscription revenue.
Accounting revenue is determined according to the company's accounting practices and may include both recurring and non-recurring revenue.
Timing can also differ.
For example, a customer may pay an annual subscription upfront, but the accounting treatment of that payment may not be identical to the way the recurring value is represented in MRR.
Founders should therefore use MRR and accounting revenue for different purposes.
MRR, ARR, Revenue, and Cash Flow: What's the Difference?
These metrics are related but should not be used interchangeably.
Understanding the distinction becomes especially important when SaaS founders move from subscription analytics into financial planning.
How RunSmart Forecasts MRR and ARR Using Stripe Data
RunSmart by Projection Genie connects Stripe subscription data with QuickBooks Online financial data to give SaaS founders a forward-looking view of both recurring revenue and the broader financial business.
Stripe provides historical information about subscription activity and recurring revenue drivers.
RunSmart uses that historical performance to establish a baseline forecast.
Founders can then model changes involving:
- Subscriber growth
- Customer churn
- Revenue churn
- Expansion revenue
- Pricing
These changes can produce different MRR and ARR trajectories.
Because RunSmart also incorporates QuickBooks financial data, the impact does not stop at recurring revenue.
Changes in the SaaS revenue forecast can flow through the broader financial model so founders can evaluate potential effects on:
- Revenue
- Profitability
- Cash flow
- Financial health
- Cash balances
- Runway
This connects SaaS operating metrics with the financial outcomes founders ultimately need to understand.
Why Forecast MRR Instead of Only Tracking It?
Tracking MRR tells a founder how recurring revenue has changed.
Forecasting MRR helps the founder understand where recurring revenue could be heading.
That distinction matters when evaluating questions such as:
- Will our current growth rate get us to $2 million ARR?
- What happens if churn rises?
- How much faster could we grow if retention improves?
- What happens if expansion increases?
- How would a pricing change affect ARR?
- Can expected recurring revenue support planned hiring?
- How would slower MRR growth affect runway?
Historical SaaS metrics provide the evidence.
Forecasting turns that evidence into a forward-looking planning tool.
Frequently Asked Questions
What is MRR?
MRR, or Monthly Recurring Revenue, is a normalized measure of recurring subscription revenue generated in a month.
What is ARR?
ARR, or Annual Recurring Revenue, expresses recurring subscription revenue on an annualized basis. For a simple monthly subscription business, ARR is commonly estimated as MRR multiplied by 12.
How do you forecast MRR?
MRR can be forecast by starting with beginning MRR and estimating future new MRR, expansion MRR, contraction MRR, and churned MRR for each period.
How do you forecast ARR?
ARR can be estimated from projected MRR by annualizing the forecast recurring revenue base. A simplified formula is Projected ARR = Projected MRR × 12.
Can Stripe data be used to forecast MRR?
Yes. Stripe subscription data can provide historical information about subscriptions, recurring revenue, churn, expansion, contraction, and pricing that can be used as inputs to an MRR forecast.
What causes MRR to increase?
MRR can increase through new subscriptions, customer expansion, higher pricing, additional seats, increased usage, or other increases in recurring customer spending.
What causes MRR to decrease?
MRR can decrease through customer churn, downgrades, reduced usage, contraction, discounts, or other reductions in recurring customer spending.
Does customer churn affect ARR?
Yes. Customer churn reduces the future recurring revenue base, which can reduce MRR and therefore annualized recurring revenue.
Is ARR the same as annual revenue?
No. ARR represents annualized recurring revenue. Total accounting revenue may include non-recurring revenue and may be recognized differently.
Is MRR the same as cash flow?
No. MRR measures recurring subscription revenue, while cash flow measures actual cash moving into and out of the business.
Should SaaS founders forecast MRR and cash flow together?
Yes. Forecasting MRR helps estimate future recurring revenue, while a broader financial forecast can show how that revenue interacts with expenses, debt, hiring, and other cash flows.
Can RunSmart forecast MRR and ARR?
Yes. RunSmart uses Stripe subscription data to establish a recurring revenue baseline and allows SaaS founders to model how changes in growth, churn, expansion, and pricing could affect future MRR and ARR.
Can RunSmart show the financial impact of MRR changes?
Yes. RunSmart combines Stripe subscription data with QuickBooks Online financial data so changes in recurring revenue can be evaluated alongside profitability, cash flow, financial health, and runway.
Turning MRR and ARR Into Forward-Looking Metrics
MRR and ARR are most useful when they do more than describe the current size of a SaaS business.
Stripe subscription data can reveal how recurring revenue has been changing through customer acquisition, churn, expansion, contraction, and pricing.
Forecasting extends those historical patterns into future periods.
RunSmart uses Stripe and QuickBooks data to establish that forward-looking baseline and lets SaaS founders model how changes to the recurring revenue engine could affect both MRR and ARR and the broader financial future of the company.
The key question becomes less:
What is our MRR today?
and more:
Where is our recurring revenue heading, and what could change that trajectory?
