Metric Definition
Customer Churn Rate
Churn rate
Churn rate measures the percentage of customers or subscribers who stop using a product or service during a given time period. It is the most direct indicator of whether a business is delivering enough ongoing value to retain its customer base, and it has a compounding effect on growth, revenue, and customer lifetime value.
9 min read
What is churn rate?
Churn rate, sometimes called attrition rate, measures how quickly customers are leaving a business. It is typically expressed as a monthly or annual percentage: if you start the month with 1,000 customers and lose 50, your monthly churn rate is 5%.
Churn is the silent killer of growth. A business adding 100 new customers per month with a 5% monthly churn rate will never grow beyond 2,000 customers because at that point new additions exactly equal losses. A business with the same acquisition rate but only 2% monthly churn will reach 5,000 customers. The difference in steady-state size is entirely driven by churn.
Churn also compounds negatively over time. A 5% monthly churn rate does not mean 60% annual churn; it means roughly 46% annual churn because each month applies to a shrinking base. But the effect on revenue is still devastating. A business that starts the year with 1,000,000 pounds in MRR and has 5% monthly churn will lose over 460,000 pounds in annual revenue from existing customers before any new sales are factored in.
This is why investors scrutinise churn so carefully. High churn indicates that the product is not delivering sustained value, that customers have better alternatives, or that the business is acquiring the wrong customers. Low churn, by contrast, signals strong product-market fit, effective customer success, and a defensible competitive position.
There are two distinct types of churn that require different measurement and different interventions. Customer churn (logo retention rate) counts the number of customers who leave. Revenue churn counts the MRR lost. A business can have low customer churn but high revenue churn if its largest customers are the ones leaving.
How to calculate churn rate
The basic churn rate formula is straightforward, but there are important variations depending on whether you are measuring customer churn or revenue churn, and how you handle mid-period additions.
- 1
Customer churn rate (logo churn)
Customer Churn Rate = (Customers Lost During Period / Customers at Start of Period) x 100. If you started the month with 500 customers and 15 cancelled, your monthly customer churn rate is 3%. This formula uses the starting count as the denominator, not the average or ending count, to avoid distortion from mid-period acquisitions.
- 2
Revenue churn rate (gross MRR churn)
Revenue Churn Rate = (MRR Lost During Period / MRR at Start of Period) x 100. This captures the financial impact of churn. If you started the month with 200,000 pounds in MRR and lost 6,000 pounds to cancellations and downgrades, your gross MRR churn rate is 3%. Revenue churn often differs from customer churn because not all customers pay the same amount.
- 3
Net revenue churn
Net Revenue Churn = ((MRR Lost - Expansion MRR from Existing Customers) / MRR at Start of Period) x 100. Net churn accounts for expansion revenue from existing customers. If your gross churn is 3% but expansion adds 2%, your net churn is 1%. Best-in-class SaaS companies achieve negative net churn, meaning existing customers generate more revenue over time even after accounting for cancellations.
- 4
Annualised churn rate
Annual Churn Rate = 1 - (1 - Monthly Churn Rate) ^ 12. Converting monthly churn to annual churn requires compounding. A 3% monthly churn rate equals roughly 31% annual churn, not 36%. This distinction matters when comparing businesses that report churn on different time frames.
Revenue churn vs customer churn
Always track both customer churn and revenue churn. If revenue churn is significantly higher than customer churn, your larger customers are leaving disproportionately, which is a more urgent problem than losing small accounts. If revenue churn is lower than customer churn, your smaller customers are churning, which may be acceptable if your strategy focuses on moving upmarket.
Churn rate in a metric tree
A metric tree decomposes churn rate into its underlying causes, transforming it from a lagging indicator into a diagnostic tool. The first-level split separates churn into voluntary and involuntary, each of which has different drivers and different solutions.
Voluntary churn occurs when customers actively decide to leave. This branch decomposes into reasons: the product does not solve their problem, they found a better alternative, their budget was cut, or they never adopted the product fully. Each reason points to a different intervention: product improvements, competitive positioning, pricing flexibility, or better onboarding.
Involuntary churn occurs when customers leave without intending to, typically due to payment failures. This is the easier branch to address because the customer still wants the product. Payment retry logic, card update reminders, and dunning sequences can recover a significant portion of involuntary churn.
Metric tree insight
Involuntary churn typically accounts for 20 to 40% of total churn in SaaS businesses. Implementing smart payment retry logic and dunning workflows can recover 30 to 50% of these failed payments, making it one of the fastest ways to reduce overall churn rate.
Churn rate benchmarks
Churn rate benchmarks depend heavily on customer segment, contract structure, and company maturity. Enterprise customers with annual contracts churn at much lower rates than SMB customers on monthly plans.
| Segment | Typical monthly churn | Typical annual churn |
|---|---|---|
| Enterprise SaaS (annual contracts) | 0.3% to 0.8% | 5% to 10% |
| Mid-market SaaS | 1% to 2% | 10% to 20% |
| SMB SaaS (monthly plans) | 3% to 7% | 30% to 60% |
| Consumer subscription | 5% to 10% | 50% to 70% |
| B2C apps (free-to-paid) | 8% to 15% | 60% to 85% |
The critical threshold for SaaS businesses is whether net revenue churn is positive or negative. Best-in-class companies achieve net negative churn, meaning expansion revenue from existing customers more than offsets losses from cancellations and downgrades. This creates a compounding growth engine where the existing customer base grows in value even without new acquisition.
For early-stage companies, churn rates above these benchmarks are acceptable while the team iterates on product-market fit. The goal at this stage is not to achieve benchmark churn but to show a clear downward trend as the product improves and the ideal customer profile becomes clearer.
How to reduce churn
Reducing churn requires a systematic approach that addresses both the immediate causes of cancellation and the upstream factors that lead customers toward the exit. The metric tree reveals where to focus.
Fix onboarding to prevent early churn
Most churn happens in the first 90 days. Customers who do not achieve their first success milestone during onboarding are 3 to 5 times more likely to churn. Identify the activation rate actions that correlate with long-term retention rate and build onboarding flows that drive those actions.
Build health scores to detect risk
Combine product usage data, support ticket frequency, NPS responses, and login patterns into a customer health score. When a score drops below a threshold, trigger proactive outreach from the customer success team before the customer decides to leave.
Recover involuntary churn with dunning
Implement smart payment retry logic that retries failed charges at optimal intervals. Send pre-emptive card expiration reminders. Use account updater services to refresh stored payment details automatically. These mechanical fixes can reduce involuntary churn by 30 to 50%.
Segment and address root causes
Analyse churn by customer segment, tenure, plan type, and cancellation reason. Different segments churn for different reasons and require different interventions. Enterprise customers may churn due to lack of integrations. SMB customers may churn due to price sensitivity.
The highest-leverage churn reduction strategies address root causes rather than symptoms. Offering discounts to customers who are about to cancel treats the symptom. Understanding why customers are not getting value and fixing the underlying product or experience issue treats the cause.
KPI Tree lets you connect churn rate to the leading indicators that predict it: login frequency, feature adoption depth, support ticket volume, and engagement trends. When customer success teams can see which branch of the churn tree is driving losses, they can intervene with the right action at the right time rather than applying generic retention tactics.
Common mistakes when tracking churn
- 1
Not separating voluntary and involuntary churn
Voluntary churn (customer chose to leave) and involuntary churn (payment failed) have completely different causes and solutions. Lumping them together makes it impossible to diagnose the problem or measure the effectiveness of interventions.
- 2
Using the wrong denominator
Churn rate should use the customer count or MRR at the start of the period as the denominator. Using the average or end-of-period count distorts the rate, especially in months with significant growth or contraction.
- 3
Comparing monthly and annual churn directly
A 5% monthly churn rate is not equivalent to 60% annual churn. Monthly churn compounds, so 5% monthly equals roughly 46% annual. Always convert to the same timeframe before comparing across companies or time periods.
- 4
Ignoring revenue churn in favour of logo churn
Losing ten small customers is very different from losing one large customer, even if the logo count is the same. Revenue churn captures the financial impact and often tells a different story than customer churn. Track both, alongside customer lifetime value to understand the full picture.
- 5
Treating churn as a single number instead of a cohort metric
Overall churn blends customers at different stages of their lifecycle. Cohort analysis reveals whether churn is concentrated in early tenure (an onboarding problem), mid tenure (a value delivery problem), or late tenure (a competitive problem). Each pattern requires a different response.
Related metrics
Churn Rate Analysis Guide
Metric Definition
An in-depth guide covering churn analysis methods, cohort analysis, and advanced reduction strategies.
Retention Rate
Product MetricsMetric Definition
Retention Rate = (Users Active at End of Period / Users Active at Start of Period) × 100
Retention rate measures the percentage of users or customers who continue to use your product over a given period. It is the most important growth metric because sustainable growth is impossible when users leave faster than they arrive.
Monthly Recurring Revenue
MRR
SaaS MetricsMetric Definition
MRR = Sum of Monthly Recurring Subscription Revenue from All Active Customers
Monthly recurring revenue (MRR) is the predictable, normalised revenue a subscription business earns each month. It is the single most important metric for understanding the health and trajectory of a SaaS company because it captures new sales, expansion, contraction, and churn in one number.
Customer Lifetime Value
CLV / LTV
SaaS MetricsMetric Definition
CLV = Average Revenue Per User × Gross Margin × Average Customer Lifespan
Customer lifetime value (CLV) is the total revenue a business can expect from a single customer account over the entire duration of their relationship. It quantifies the long-term financial worth of acquiring and retaining a customer, making it one of the most important metrics for sustainable growth.
Decompose churn rate and find your retention levers
Build a churn rate metric tree that separates voluntary from involuntary churn, connects each cause to leading indicators, and assigns clear ownership to every branch.