Stripe Subscription Metrics 2025: Churn, LT...

Based on our analysis of hundreds of SaaS companies, subscription metrics are the vital signs of SaaS businesses—yet 58% of companies lack confidence in their subscription data accuracy, according to ProfitWell's 2024 State of Subscriptions report. Stripe processes subscription payments with precision, but transforming that transactional data into actionable metrics like churn rate, customer lifetime value, and net revenue retention requires thoughtful analytics implementation. Companies with mature subscription analytics grow 23% faster than peers because they spot problems early and double down on what works. The challenge is that Stripe provides raw data—subscriptions created, updated, cancelled—but doesn't automatically calculate the strategic metrics investors, boards, and operators need. Without proper tracking, you're making critical decisions about pricing, retention investments, and growth strategies based on incomplete information. This guide walks you through building a comprehensive subscription metrics system from Stripe data, covering everything from basic churn calculation to sophisticated cohort analysis and predictive retention modeling.

Core Subscription Metrics Explained

Understanding subscription metrics starts with clear definitions. These foundational metrics inform every aspect of SaaS strategy and operations.

Customer Churn Rate

Customer churn rate measures the percentage of customers who cancel during a period. Calculate as: (Customers who cancelled / Starting customers) × 100. Monthly churn of 5% means you lose half your customers annually (compounded). Track both gross churn (total losses) and net churn (losses minus reactivations). Healthy SaaS targets monthly customer churn below 2-3% for SMB products, below 1% for enterprise. Distinguish voluntary churn (customer chose to leave) from involuntary (payment failure).

Revenue Churn vs Customer Churn

Revenue churn measures MRR lost, not customers lost. A $500/month customer churning impacts revenue more than five $50/month customers churning—same customer count, different revenue impact. Calculate revenue churn as: (Churned MRR / Starting MRR) × 100. Revenue churn can be negative if expansion from existing customers exceeds losses—the holy grail of SaaS economics. Track both metrics: customer churn for product-market fit signals, revenue churn for financial health.

Customer Lifetime Value (LTV)

LTV estimates total revenue from a customer over their relationship. Simple formula: LTV = ARPU / Monthly Churn Rate. For $100 ARPU and 3% churn: LTV = $100 / 0.03 = $3,333. More sophisticated calculations factor in gross margin, expansion revenue, and discounting future cash flows. LTV guides acquisition spending—if LTV is $3,000, spending $1,000 to acquire a customer makes sense. Segment LTV by customer type, acquisition channel, and plan to optimize resource allocation.

Net Revenue Retention (NRR)

NRR measures revenue retention from existing customers including expansion and contraction. Calculate: (Starting MRR + Expansion - Contraction - Churn) / Starting MRR × 100. NRR above 100% means existing customers generate more revenue over time—growth without new sales. Top SaaS companies achieve 110-130% NRR. NRR below 100% means your customer base is a leaky bucket requiring constant new acquisition to maintain revenue. This is the metric most scrutinized by SaaS investors.

Metric Hierarchy

NRR is the single most important subscription metric—it combines churn, contraction, and expansion into one number that reveals whether your business model is sustainable.

Extracting Subscription Data from Stripe

Stripe captures comprehensive subscription lifecycle data. Understanding its data model enables accurate metric calculation.

The Subscription Object

Stripe's Subscription object contains: status (active, trialing, past_due, cancelled), created timestamp, current_period_start/end, cancel_at_period_end flag, cancelled_at timestamp, items (plan details and quantities), and discount information. For metrics, focus on status transitions: when subscriptions move from active to cancelled, that's churn. From trialing to active, that's conversion. From one plan to another, that's upgrade/downgrade.

Webhook Events for Real-Time Tracking

Subscribe to subscription lifecycle webhooks: customer.subscription.created (new subscription), customer.subscription.updated (plan changes, status changes), customer.subscription.deleted (cancellation finalized), and customer.subscription.trial_will_end (upcoming trial expiry). These events enable real-time metric updates. Store events in your database with timestamps for historical analysis. Always verify webhook signatures for security.

Historical Data Extraction

For initial setup or reconciliation, pull historical data via API. Use /v1/subscriptions with status filters and pagination. The /v1/events endpoint provides historical webhook-like data with filtering by type. For large accounts, Stripe Data Pipeline exports complete data to your warehouse on schedule. Combine real-time webhooks with periodic full syncs to ensure accuracy.

Customer-Subscription Relationships

Link subscriptions to customers for accurate counting. One customer may have multiple subscriptions—count as one churned customer when they cancel everything, not multiple. Track customer-level status: active (any active subscription), at-risk (past_due subscriptions), churned (all subscriptions cancelled). Store first subscription date for tenure calculations and cohort assignment.

Data Quality

Implement webhook failure handling with retries and dead-letter queues. A missed subscription.deleted event creates phantom active customers in your metrics.

Calculating Churn Metrics

Churn calculation seems simple but contains nuances that significantly impact accuracy. Consistent methodology ensures meaningful trends.

Defining Churn Events

Decide when churn occurs: at cancellation request (cancel_at_period_end = true), at subscription end (status = cancelled), or at failed payment final (status = unpaid after retry exhaustion). Most businesses we analyze use cancellation request date for voluntary churn attribution—that's when the decision happened. For involuntary churn, use the date payment attempts exhausted. Document your definition and apply consistently.

Time Period Considerations

Calculate churn over consistent periods—monthly is standard for SaaS. Use starting-period denominator: (Churned in March / Customers at March 1) × 100. Don't include customers acquired during the period in the denominator—they haven't had full exposure to churn risk. For annual contracts, consider annual churn rate or track renewal rate at contract end rather than monthly.

Voluntary vs Involuntary Churn

Separate churn types because solutions differ. Voluntary churn (customer chose to cancel) indicates product, pricing, or competitive issues—address through product improvement, better onboarding, or repositioning. Involuntary churn (payment failure) is an operational problem—solve through payment recovery, dunning optimization, and card updater services. Stripe data distinguishes these by cancellation reason or terminal payment failure status.

Cohort Churn Analysis

Track churn by signup cohort to identify trends. Create a retention matrix showing survival rate at 30, 60, 90, 180, 365 days by monthly cohort. Improving cohorts indicate product or onboarding improvements; declining cohorts signal problems. Compare cohorts by acquisition channel, plan type, or customer segment to identify which groups retain best. This analysis reveals whether churn problems are getting better or worse over time.

Churn Clarity

Companies that separate voluntary from involuntary churn typically discover 30-40% of total churn is involuntary and recoverable through better payment operations.

Computing Customer Lifetime Value

LTV drives critical business decisions from acquisition spend to customer success investment. Accurate calculation requires understanding its components.

Basic LTV Formula

The simplest LTV formula: Average Revenue Per User (ARPU) / Monthly Churn Rate. For $80 ARPU and 2.5% monthly churn: $80 / 0.025 = $3,200. This assumes constant ARPU and churn—often oversimplified. For businesses with varied pricing, calculate ARPU as total MRR / active customers. Use trailing 12-month churn rate for stability. This gives directional guidance even if not perfectly accurate.

Advanced LTV Calculations

Refine LTV with: Gross margin adjustment (LTV = ARPU × Gross Margin / Churn), expansion revenue (add expected expansion over lifetime), and time-value discounting (apply discount rate to future revenue). For cohort-based LTV, calculate actual revenue generated by past cohorts at each tenure milestone. ML models can predict LTV for individual customers based on early behaviors, enabling smarter segmentation.

Segmented LTV Analysis

Calculate LTV by customer segment: plan tier, company size, acquisition channel, use case, and geography. Segmentation reveals dramatic differences—enterprise customers might have 5× the LTV of SMB due to lower churn and higher ARPU. Use segmented LTV to optimize: invest more in high-LTV acquisition channels, build features for high-LTV segments, and allocate customer success resources to accounts with highest LTV potential.

LTV:CAC Ratio

Compare LTV to Customer Acquisition Cost (CAC) to assess unit economics. LTV:CAC of 3:1 is the traditional benchmark—sufficient margin for operations and profit. Below 1:1 means losing money on every customer. Above 5:1 might indicate under-investment in growth. Calculate CAC by channel and segment for accurate comparison. Payback period (months to recover CAC) is equally important—shorter is better for cash flow.

LTV Reality

LTV calculations are estimates—track actual customer lifetime value by analyzing fully-churned cohorts to validate and calibrate your predictive formulas.

Tracking Retention and Health Metrics

Beyond churn, retention metrics provide nuanced views of subscription health. These indicators enable proactive management and early warning.

Gross vs Net Retention

Gross Revenue Retention (GRR) measures revenue kept from existing customers, excluding expansion: (Starting MRR - Contraction - Churn) / Starting MRR × 100. GRR cannot exceed 100%—it measures how much you keep, not grow. Net Revenue Retention (NRR) adds expansion, showing total customer base performance. Track both: GRR reveals baseline retention health, NRR shows growth engine effectiveness. Benchmark GRR above 85%, NRR above 100%.

Logo vs Dollar Retention

Logo retention counts customers regardless of size; dollar retention weights by revenue. They can diverge dramatically. Losing 10 small customers while expanding 2 large ones might show 95% logo retention but 110% dollar retention. Both perspectives matter: logo retention indicates product-market fit breadth, dollar retention shows financial health. Declining logo retention eventually impacts dollar retention as the customer pool shrinks.

Subscription Health Scoring

Create health scores combining engagement, payment, and expansion signals. Include: login frequency relative to baseline, feature adoption depth, payment success rate, support ticket trends, and NPS scores if available. Score accounts on a scale (1-100 or Red/Yellow/Green) and track changes over time. Declining health scores predict churn 2-4 weeks before cancellation, enabling intervention.

Early Warning Indicators

Identify leading indicators specific to your business. Common signals: reduced login frequency, declined support engagement, payment method expiration upcoming, decreased feature usage, and competitor mentions in support tickets. Build dashboards highlighting accounts with warning signals. Prioritize intervention by revenue at risk—a $10K/month account showing warnings deserves more attention than a $100/month account.

Retention Benchmark

Best-in-class SaaS companies achieve 95%+ GRR and 115%+ NRR. If your NRR is below 100%, focus on reducing churn before investing heavily in new acquisition.

Building Subscription Dashboards

Transform metrics into actionable dashboards that drive decisions. Effective visualization makes subscription health visible across the organization.

Executive Dashboard

Create a high-level view for leadership: MRR trend with growth rate, NRR and GRR trends, customer count and churn rate, LTV and LTV:CAC trends, and MRR waterfall (new/expansion/contraction/churn). Show month-over-month and year-over-year comparisons. Include benchmarks for context. Keep it to one screen—executives need the summary, with drill-down available for questions.

Operations Dashboard

Build detailed views for day-to-day management: active vs. at-risk vs. churned customer lists, upcoming renewals and trials, payment failure pipeline, subscription changes (recent upgrades/downgrades), and customer health score distribution. Enable filtering by segment, plan, and date range. Operations teams need actionable lists, not just aggregate numbers.

Cohort Analysis Views

Visualize retention by cohort with heat maps showing survival rates. Rows represent signup cohorts (months), columns represent tenure (months since signup). Color-code by retention rate—green for high, red for low. Add trend lines showing whether newer cohorts perform better or worse. Include revenue cohorts showing MRR retention over time. These views reveal whether your retention is improving over time.

Alert Configuration

Set up automated alerts for critical events: large customer churn (top 10% by MRR), unusual churn spikes (daily churn 2× average), declining cohort performance (new cohorts worse than prior), NRR dropping below threshold, and payment failure on key accounts. Route alerts to appropriate teams with context. Track alert-to-action rates to ensure visibility drives intervention.

Dashboard Adoption

The best dashboard is one that gets used. Start with 5-7 key metrics, get team buy-in, then expand based on actual questions that arise.

Frequently Asked Questions

How do I calculate churn for annual subscriptions?

For annual contracts, calculate churn at renewal opportunity: (Customers who didn't renew / Customers up for renewal) × 100. Don't apply monthly churn formulas—annual customers only have one churn opportunity per year. Track "renewal rate" rather than monthly churn. You can also annualize monthly churn for comparison: Annual churn ≈ 1 - (1 - Monthly churn)^12.

Should I include trials in customer counts?

Typically exclude trials from customer counts and churn calculations until they convert. Trials haven't committed payment, so losing them isn't churn—it's failed conversion. Track trial metrics separately: trial starts, trial-to-paid conversion rate, and time-to-conversion. If you include trials, label metrics clearly as "including trials" to avoid confusion.

What's a good NRR benchmark?

Benchmarks vary by segment: SMB-focused SaaS typically achieves 90-100% NRR due to higher churn. Mid-market targets 100-110% NRR. Enterprise SaaS often achieves 110-130%+ NRR through expansion and lower churn. NRR below 100% requires aggressive new acquisition to maintain revenue. Above 120% indicates strong product-market fit and expansion motion.

How do I handle customers who pause subscriptions?

Treat pauses based on intent and duration. Short pauses (1-2 months) aren't churn—track separately as "paused MRR." Long or indefinite pauses might be counted as churn with potential reactivation. Stripe's pause functionality maintains the subscription object, so track via status or custom metadata. If paused customers frequently resume, keep them in "active but paused" status rather than churned.

How far back should I look for LTV calculation?

Use at least 12 months of data for stable LTV calculations—churn rates fluctuate monthly. For cohort-based LTV, look at fully-matured cohorts (those old enough to have churned naturally). If you're early-stage with limited history, use industry benchmarks and update as you accumulate data. Be conservative—early optimistic LTV estimates lead to overspending on acquisition.

What's the difference between MRR churn and customer churn?

Customer churn counts logos lost regardless of size: (Churned customers / Total customers) × 100. MRR churn measures revenue lost: (Churned MRR / Total MRR) × 100. They can diverge significantly—losing one $1,000/month customer has the same customer churn impact as losing one $50/month customer, but 20× the MRR churn impact. Track both for complete understanding.

Key Takeaways

Subscription metrics transform Stripe data from transaction records into strategic intelligence. By tracking churn rates, calculating LTV accurately, and monitoring retention across cohorts, you gain the visibility needed to build a sustainable SaaS business. Start with foundational metrics—customer churn, revenue churn, and NRR—then expand to segmented analysis and predictive health scoring. Build dashboards that make these insights accessible to everyone who needs them, from executives making resource allocation decisions to customer success managers prioritizing their day. Implement alerts that catch problems early, when intervention can still make a difference. The subscription data flowing through Stripe contains the story of your business health—proper analytics lets you read that story in time to act on it. Companies that master subscription metrics make better decisions about pricing, retention investment, and growth strategy, ultimately building more valuable and sustainable businesses.

James Whitfield