A 5% monthly churn rate means you lose half your customer base every year. Most SaaS founders track churn as a single percentage in their metrics spreadsheet, but that number hides everything that matters: which plan tier is hemorrhaging, which accounts are walking out the door this quarter, and how much MRR is at risk right now. This analysis takes your Stripe subscription export and turns it into a prioritized list of accounts your customer success team should call today.
Why Churn Is the Silent Killer of SaaS Growth
You can grow new MRR by 10% every month and still flatline if churn eats the gains. According to 2026 benchmarks, the median B2B SaaS company churns 3-5% of SMB customers monthly, 1.5-3% mid-market, and 1-2% enterprise (UserJot, 2026). Best-in-class companies hold monthly churn below 1%. The difference between 2% and 5% monthly churn does not sound dramatic until you compound it: at 2%, you retain 78% of customers annually; at 5%, you retain only 54%.
The real problem is not the rate itself -- it is that most founders cannot answer three basic questions: Which customers are about to leave? How much revenue is walking out with them? And which plan tier needs the most urgent attention? Stripe shows you cancellation counts after the fact. This analysis shows you the risk before it becomes a loss.
Dedicated churn prediction platforms like ChurnAssassin, Userpilot, or Gainsight cost $200-2,000 per month and require product instrumentation -- event tracking, feature usage logging, health scoring integrations. If you are a post-PMF SaaS company at $100K-$10M ARR, you probably have not built that instrumentation yet. But you do have billing data. This analysis works from a Stripe CSV export you can pull in two minutes.
What This Analysis Tells You
The report answers the questions that matter for operational decisions, not academic curiosity. Here is what you get and how to use each piece.
Churn rate by plan tier. Your Basic plan at $29/month and your Enterprise plan at $199/month do not churn at the same rate. They almost never do. This analysis breaks churn by tier so you can see where retention investment has the highest ROI. A common finding: the cheapest tier churns at 3-4x the rate of the most expensive one. If your Basic plan accounts for 50% of cancellations but only 10% of MRR, the math says focus retention spend on higher tiers.
MRR at risk. This converts churn from a percentage into dollars. Knowing you have $14,000 in MRR from past_due subscriptions and accounts scheduled for cancellation at period end puts a price tag on inaction. It also gives you a concrete number for your board deck: "we have $14K in MRR at risk this month, and here is what we are doing about it."
At-risk subscription list. This is the most operationally valuable output. The report flags every subscription that is past_due, has cancellation scheduled at period end, or is approaching a typical churn window based on subscription age. Each entry includes plan name, amount, and subscription age -- giving your customer success team a sorted outreach list ranked by revenue at stake.
Subscription age at cancellation. Most cancellations do not happen randomly across the lifecycle. They cluster. In many SaaS businesses, 80% of cancellations happen in the first 90 days. If your data shows a month-2 cliff, your onboarding is failing. If churn is steady across all ages, you have a product-market fit problem, not an onboarding problem. The distinction matters because the fix is completely different.
Trial-to-paid conversion rates. If you use trial periods, this analysis shows what percentage convert and whether trial-origin subscribers churn differently than direct subscribers. Some businesses find that free trials attract tire-kickers who churn fast. Others find that trials filter out bad-fit customers, leading to better long-term retention. The data resolves the debate.
When to Run This Analysis
- Quarterly, for board reporting -- gross churn rate, net revenue retention, and MRR at risk are metrics every SaaS investor scrutinizes
- After a pricing change -- measure whether the new structure is affecting retention by tier
- Before budgeting season -- forecast expected revenue loss and justify retention investment
- When customer success capacity is limited -- the at-risk list prioritizes who to call first based on revenue at stake
- After launching a new plan or feature -- compare churn rates for customers who adopted versus those who did not
What Data Do You Need?
A CSV export from Stripe. Go to your Stripe Dashboard, navigate to Billing, then Subscriptions, and click Export. The analysis requires five columns and supports six optional columns that unlock deeper insights.
Required columns
- Status -- active, canceled, past_due, trialing, or unpaid
- Plan name -- Basic, Pro, Enterprise, or whatever your tiers are called
- Plan amount -- price in cents (Stripe's default: 4900 = $49.00)
- Billing interval -- month or year
- Created date -- when the subscription started
Optional columns (recommended)
- Canceled date -- when the subscription was actually canceled (more precise than inferring from status)
- Cancel at period end -- whether cancellation is scheduled but has not happened yet (critical early warning)
- Trial start/end dates -- enables trial conversion analysis
- Seat quantity -- for per-seat SaaS products, weights churn by account size
- Billing method -- charge_automatically vs. send_invoice (invoice-billed accounts sometimes churn differently)
Minimum: 100 subscriptions. The analysis works best with 500 or more subscriptions and at least six months of history, so survival curves have enough data to stabilize. Works with Chargebee, Recurly, Paddle, or any system that exports equivalent columns.
How to Read the Report
Churn Executive Summary -- your top-line numbers: overall churn rate, total MRR, MRR at risk, and number of at-risk subscriptions. This is the board slide. If only one number matters, it is MRR at risk -- it translates churn from a percentage into dollars you are about to lose.
Subscription Status Distribution -- breakdown of your subscriber base by status. A healthy business has a large active segment and a small canceled segment. If past_due is growing, you have a payment recovery problem separate from voluntary churn.
MRR by Plan and Status -- cross-tabulates revenue by plan tier and subscription status. You might discover Enterprise contributes 60% of MRR but only 15% of churn, while Basic generates 10% of MRR but accounts for half of all cancellations.
Churn Risk by Plan Tier -- churn rates segmented by plan. This card usually produces the biggest surprises. A six-fold difference between Basic and Enterprise churn is common and demands different retention strategies for each tier.
Subscription Age Distribution -- shows when in the lifecycle customers cancel. Survival analysis tells us churn risk is usually highest in the first 30-90 days and drops sharply after. A spike at month 2 means onboarding is failing. Steady churn across all ages means the product itself is the problem.
At-Risk Subscriptions -- individual accounts flagged for cancellation or in past_due state, sorted by revenue at stake. This is the list your CS team works from.
What to Do With the Results
Immediate actions
- Call the top 10 at-risk accounts -- start with the highest-MRR subscribers who are past_due or have cancellation scheduled. A 15-minute check-in call saves more revenue than any automated email sequence.
- Fix involuntary churn first -- past_due subscriptions are failed payments, not unhappy customers. Implement dunning (retry logic + email sequences). This is the cheapest revenue to recover.
- Quantify the board slide -- "We have $X MRR at risk this month. Here are the 3 actions we are taking." Boards respond to dollars, not percentages.
Strategic actions
- Design tier-specific retention programs -- if Basic churns at 8% monthly and Enterprise at 1%, those segments need fundamentally different retention approaches
- Fix the onboarding cliff -- if most cancellations happen in the first 90 days, invest in activation (first-value delivery), not long-term engagement programs
- Evaluate trial strategy -- if trial-origin subscribers churn faster than direct subscribers, your trial may be attracting tire-kickers rather than filtering for fit
When to Use Something Else
- Want to see retention trends across signup cohorts: Use cohort retention analysis -- it shows whether newer cohorts retain better than older ones, which tells you if your product is improving.
- Want to understand MRR composition and growth trends: Use MRR analysis -- it decomposes revenue into new, churned, and net movement so you can see the full growth picture.
- Want to predict which individual customers will churn using behavioral signals: Build a classification model with logistic regression or XGBoost if you have product usage data. This analysis works from billing data alone.
- Want to segment customers by value for targeted campaigns: Use RFM segmentation -- it groups customers by recency, frequency, and monetary value.
References
- SaaS Churn Rate Benchmarks: What's Actually Normal in 2026. UserJot. userjot.com
- SaaS Churn Benchmarks for 2026. Shno. shno.co
- B2B SaaS Churn Rate Benchmarks. Vitally. vitally.io
- B2B SaaS Churn Rates -- 33 Statistics Every Marketing Leader Should Know in 2026. Genesys Growth. genesysgrowth.com