Published on 2025-06-26T05:11:11Z

What is Customer Churn Rate? Examples and Calculation

Customer Churn Rate is a metric in analytics that measures the percentage of customers who discontinue using a product or service within a given time frame. This term is particularly crucial for subscription-based business models, SaaS providers, and any organization relying on repeat customers. By tracking churn, businesses can diagnose underlying issues such as product dissatisfaction, poor onboarding, or billing failures and implement targeted retention strategies. A rising churn rate can signal urgent problems in user experience or value proposition, while a stable or declining rate often reflects successful customer engagement practices. Analytic tools like Plainsignal and Google Analytics 4 can facilitate detailed churn analysis through cohort reports and custom calculations, empowering teams to take data-driven actions to strengthen customer loyalty.

Illustration of Customer churn rate

Customer churn rate

The percentage of customers lost over a specific period, revealing retention health and guiding strategies to reduce attrition.

Definition and Importance

Customer Churn Rate is a metric in analytics that measures the percentage of customers who discontinue using a product or service within a given time frame. This term is particularly crucial for subscription-based business models, SaaS providers, and any organization relying on repeat customers. By tracking churn, businesses can diagnose underlying issues such as product dissatisfaction, poor onboarding, or billing failures and implement targeted retention strategies. A rising churn rate can signal urgent problems in user experience or value proposition, while a stable or declining rate often reflects successful customer engagement practices. Analytic tools like PlainSignal and Google Analytics 4 can facilitate detailed churn analysis through cohort reports and custom calculations, empowering teams to take data-driven actions to strengthen customer loyalty.

What is customer churn rate?

Customer Churn Rate measures the percentage of customers who stop doing business with a company over a specific period. It shows the portion of the customer base lost and is key for subscription-based or repeat-purchase models.
Why it matters

A high churn rate indicates issues in customer satisfaction, product fit, or engagement. Reducing churn is often more cost-effective than acquiring new customers, making it vital for growth and profitability.
Types of churn

Churn can be voluntary (customers choosing to leave) or involuntary (lost payment methods, failed renewals). Distinguishing these helps tailor retention strategies.
- Voluntary churn:
  Occurs when a customer actively decides to cancel or stop using a service.
- Involuntary churn:
  Results from failed payments, account closures, or other system-driven cancellations.

Calculating Churn Rate

Accurate calculation of churn rate is foundational for tracking customer retention over time. Businesses typically measure churn monthly, quarterly, or annually. Consistent calculation methods ensure meaningful trends and benchmark comparisons. Different analytics platforms offer distinct ways to define, extract, and compute churn data, from custom formulas to cohort analyses.

Basic formula

Churn Rate = (Number of Customers Lost During Period ÷ Number of Customers at Start of Period) × 100. Use consistent time frames (monthly, quarterly, yearly) for meaningful comparisons.
Example in ga4
GA4 doesn’t provide churn rate out-of-the-box, but you can approximate it by creating custom audiences or using BigQuery export:
1. Export user-level data to BigQuery.
2. Identify users active in the start period and absent in the subsequent period.
3. Calculate (lost users ÷ initial users) × 100 within your reporting tool (e.g., Looker Studio).
Example in plainsignal
With PlainSignal’s cookie-free analytics, you can track user retention cohorts and compute churn directly:
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Navigate to the ‘Retention’ report, select your cohort period, and the dashboard will show the percentage of users who didn’t return, which is your churn rate.

Strategies to Reduce Churn

Reducing churn requires proactive measures across the customer lifecycle, from onboarding to ongoing engagement. Implementing data-driven strategies can enhance satisfaction, increase product adoption, and build long-term loyalty.

Improve onboarding experience

Make the initial experience smooth and educational through tutorials, tooltips, and personalized welcome flows. A strong start reduces early churn.
Engage with customers proactively

Use automated email campaigns, in-app messages, and push notifications to keep users informed of new features and best practices.
Offer responsive support

Implement easily accessible support channels (chat, email, phone) and a comprehensive knowledge base to address issues quickly.
Gather and act on feedback

Regularly survey users, analyze support tickets, and act on insights to improve product features and satisfaction.

Use Cases and Best Practices

Leveraging churn data effectively involves benchmarking, cohort analysis, and targeted segmentation. Best practices help in understanding underlying drivers and optimizing retention efforts.

Benchmarking against industry standards

Compare your churn rate to industry averages to gauge performance. Different sectors have varying acceptable churn thresholds.
Cohort analysis

Analyze churn by user cohorts based on signup date, feature adoption, or plan type to identify at-risk segments and tailor retention strategies.
Customer segmentation

Segment churn data by demographics, behavior, or revenue to uncover patterns and focus on high-value or at-risk groups.

Customer churn rate

Definition and Importance