Monthly Recurring Revenue is the single number that tells you whether your subscription business is growing, stalling, or shrinking. But the top-line MRR figure hides everything that matters: how much of that revenue is new, how much you lost to churn, which plan tiers are pulling their weight, and whether your average customer is worth more this month than last. Upload your Stripe subscription export and get a full MRR decomposition — trend lines, churn rates, ARPU, plan-level breakdowns, and AI insights — in under 60 seconds.
What Is MRR and Why Does It Matter?
Monthly Recurring Revenue (MRR) is the total predictable revenue your subscription business generates each month, normalized to a monthly basis. A customer on a $49/month plan contributes $49 to MRR. A customer on a $588/year plan contributes $49/month. MRR strips out one-time charges, usage-based overages, and timing differences to give you the clearest possible picture of your revenue engine.
For SaaS companies, MRR is the metric investors, board members, and operators all look at first. It answers the most basic question: is this business growing? But the raw number only tells part of the story. A company with $50,000 MRR could be adding $8,000 in new subscriptions each month while losing $7,500 to cancellations — net growth of just $500 that masks serious churn. Or it could be adding $3,000 with only $500 in churn — slower gross growth but far healthier fundamentals. You cannot make good decisions without decomposing MRR into its components.
This analysis takes your Stripe subscription data, computes MRR for every month in your history, and breaks the movement into the pieces that matter: new MRR from first-time subscribers, churned MRR from cancellations, and the net change. It also calculates churn rate, average revenue per user (ARPU), and segments everything by plan tier so you can see which products drive your business.
What the Report Shows You
MRR Growth Trend
The MRR trend chart plots your total monthly recurring revenue over time as a line chart. This is the headline view — the shape of this line tells the story of your business. A steadily rising line means your growth engine is working: new subscriptions consistently outpace cancellations. A flattening line is the earliest warning sign that growth is stalling, often months before it shows up in quarterly revenue. A declining line means churn is winning, and you need to act.
The report computes your current MRR and month-over-month growth rate as headline KPIs. For a SaaS business with product-market fit, healthy MoM growth typically runs between 5% and 15% in early stages, tapering to 2-5% as the base gets larger. If you are growing at 1% or less, it usually means your acquisition barely covers churn — the "leaky bucket" problem that no amount of marketing spend can solve without fixing retention.
MRR Movement: New vs. Churned
The MRR movement chart is a grouped bar chart showing new MRR and churned MRR side by side for each month. This is where the real story lives. A month where you added $12,000 in new MRR but lost $9,000 to churn looks like $3,000 net growth on the trend line — respectable until you see that 75% of your effort went to replacing lost revenue rather than growing.
SaaS operators call this MRR growth decomposition. In a fully instrumented system, you would further split this into new MRR (brand-new customers), expansion MRR (existing customers upgrading or adding seats), contraction MRR (downgrades), and churn MRR (cancellations). With Stripe subscription exports, the analysis tracks new subscriptions versus cancellations directly. If a customer upgrades from Basic to Pro, it appears as one cancellation and one new subscription — the net effect on MRR is captured correctly, even though the decomposition attributes it differently than event-level data would.
Watch for months where churned MRR exceeds new MRR. Even one month of negative net MRR deserves investigation. Was there a price increase? A product outage? A competitor launch? Seasonal patterns in B2B (year-end budget cuts) or B2C (post-holiday cancellations) can also explain spikes. The chart makes these patterns visible at a glance.
Revenue by Plan Tier
The plan breakdown chart shows current MRR contribution by subscription tier as a horizontal bar chart. This answers a question every SaaS founder needs to confront: where does the money actually come from? A company with three tiers — Basic at $19/month, Pro at $49/month, and Enterprise at $199/month — might discover that Enterprise accounts with only 8% of subscribers generate 40% of total MRR. Or that the Basic tier has the most subscribers but contributes the least revenue and the highest churn.
The accompanying plan summary table shows subscriber count, total MRR, and average revenue per subscriber for each tier. This is critical for pricing decisions. If your Pro plan has high adoption but ARPU is clustered near the low end of the tier, you might have room to introduce a mid-tier. If Enterprise has low adoption but high retention, doubling down on enterprise sales could be more efficient than acquiring ten Basic customers who churn in three months.
Churn Rate Analysis
The churn trend chart plots monthly subscriber churn rate — the percentage of active subscribers who cancelled in each month. For subscription businesses, churn rate is arguably more important than growth rate, because churn compounds. A 5% monthly churn rate means you lose roughly 46% of your customer base every year. Even a 3% monthly rate means annual churn of 31%. The commonly cited benchmark is below 2% monthly for healthy SaaS — and best-in-class companies targeting enterprise customers often achieve below 1%.
The chart makes trends and anomalies obvious. A creeping increase from 2% to 4% over six months is a structural problem — something about the product, pricing, or onboarding is deteriorating. A single spike to 8% in one month is an event — a billing error, a competitor promotion, or a cohort of trial conversions that were never truly activated. The distinction matters because the fix is completely different: structural problems need product work, while event-driven spikes need targeted retention campaigns.
Monthly Metrics Table
The comprehensive monthly metrics table brings everything together in one view: total MRR, active subscribers, new subscriptions, cancellations, churn rate, ARPU, and month-over-month growth for every month in your dataset. This is the table you pull up in board meetings, paste into investor updates, or hand to your finance team. Every number is computed from your actual Stripe data — no sampling, no estimation.
SaaS KPI Summary
The headline metrics card shows your four most important numbers at a glance: current MRR, month-over-month growth rate, current churn rate, and ARPU. These are the vital signs of a subscription business. If you only have 30 seconds to check on your business health, these four numbers tell you whether things are on track or whether something needs attention.
What Data Do You Need?
You need a Stripe subscription export as a CSV file. The required columns are: subscription ID, customer ID, plan name (the tier or product name), plan amount (in cents — Stripe's default format, where $49.00 is stored as 4900), billing interval (month or year), subscription status (active, canceled, or trialing), subscription creation date, and cancellation date (blank for active subscriptions).
To export from Stripe: go to your Stripe Dashboard, navigate to Billing then Subscriptions, and use the Export button to download a CSV. The export includes all the columns this analysis needs. If you use a billing platform that wraps Stripe (like Chargebee, Recurly, or Paddle), export your subscription data in CSV format with equivalent columns — the tool maps column names during upload, so exact header names do not matter.
For meaningful results, you need at least 10 subscriptions spanning 3 or more months. The analysis works best with 50+ subscriptions and 6+ months of history, which gives enough data points for trend lines and churn rates to be statistically meaningful. With fewer than 20 subscriptions, month-to-month percentages will be volatile — two cancellations out of fifteen active subscribers is a 13% churn rate, which looks alarming but may just be normal variance in a small base.
One common pitfall: Stripe stores amounts in cents (the smallest currency unit). If your export already shows dollar amounts ($49.00 rather than 4900), the analysis will detect this and adjust. But if you have manually converted values, double-check that your MRR output matches your Stripe dashboard. The report should reconcile within 5% of your Stripe-reported MRR — any larger discrepancy usually means a currency unit issue or that trial subscriptions are being included.
Real-World Examples
SaaS Startup Board Reporting
A B2B SaaS company with three pricing tiers runs this analysis monthly to prepare board materials. The MRR trend shows growth from $12,000 to $31,000 over nine months. But the movement chart reveals that churn accelerated in months 7-9 as early cohorts reached their renewal decision. The board sees not just "we grew 158%" but "growth is real, and now retention is the priority." The company shifts engineering resources from new features to onboarding improvements.
Expansion vs. Contraction Revenue
A developer tools company notices their MRR trend is flat despite strong new customer acquisition. The MRR movement chart shows $6,000 in new MRR each month — but also $5,500 in churned MRR. Digging into the plan breakdown, they find that Enterprise accounts have near-zero churn while Basic plan subscribers churn at 8% monthly. The insight: their product delivers clear value at scale but the Basic tier does not give small teams enough to justify continued payment. They redesign the Basic plan to include features that drive daily usage.
Net Revenue Retention Tracking
A subscription e-commerce platform uses the monthly metrics table to track whether existing customers are spending more or less over time. By comparing ARPU trends against subscriber counts, they identify that ARPU is rising 2% monthly — customers are upgrading to higher tiers without prompting. This is a sign of strong product-market fit and suggests the company should invest in making upgrade paths more visible, since organic expansion is already happening.
Post-Price-Change Impact
A SaaS company raises prices by 20% and needs to measure the impact. The churn trend chart shows a spike from 2.1% to 4.8% in the month after the increase, followed by a decline to 2.5% in the next month. Meanwhile, MRR actually increased because the higher price per subscriber more than offset the churn spike. The monthly metrics table lets them calculate the exact tradeoff: they lost 14 subscribers but gained $2,300 in net MRR. The price increase was worth it — but only because churn returned to baseline quickly.
When to Use Something Else
MRR analysis tells you what happened — it is descriptive, not predictive. If you want to predict which specific customers are likely to churn next month so you can intervene, use churn prediction. That module builds a predictive model using subscription features and flags at-risk accounts before they cancel.
If you want to understand retention patterns across signup cohorts — do January signups retain better than March signups, and why? — use cohort retention analysis. Cohort analysis groups customers by when they started and tracks their behavior over time, which reveals whether your retention is improving or degrading across acquisition periods.
If you need to forecast future MRR rather than analyze historical trends, use a time series forecasting tool like ARIMA or Prophet. These models project your MRR trajectory forward with confidence intervals, accounting for trend and seasonality. You can feed them the monthly MRR values from this analysis as input.
If your goal is understanding the total lifetime value of a customer to inform acquisition spend, use LTV analysis. LTV combines average revenue per user with churn rate to estimate how much revenue a typical customer generates over their entire relationship — a different question than "what is my MRR right now?"
And if your data is one-time purchases rather than recurring subscriptions — for example, a Shopify store without a subscription product — MRR analysis does not apply. Use Stripe revenue analysis or revenue trend analysis for non-recurring revenue patterns.
The R Code Behind the Analysis
Every report includes the exact R code used to produce the results — reproducible, auditable, and citable. This is not AI-generated code that changes every run. The same data produces the same analysis every time.
The analysis normalizes all subscription amounts to monthly values (dividing annual plans by 12), computes active subscriber counts per month using subscription start and cancellation dates, and aggregates MRR by summing normalized amounts across active subscriptions. Churn rate is calculated as cancellations divided by the prior month's active subscriber count. ARPU is total MRR divided by active subscribers. Every metric follows standard SaaS accounting definitions. The code is visible in the R Code tab of your report, so you or your finance team can verify exactly how each number was computed.