E-commerce churn rate benchmarks show how often customers or subscribers stop buying from a store. This page separates subscription churn from non-subscription repeat-purchase churn and gives practical ranges for retention analysis.
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This page belongs to the Customer Retention silo. For retention economics, compare it with
repeat purchase rate benchmarks,
LTV benchmarks,
CAC benchmarks,
LTV to CAC benchmarks,
churn rate benchmarks
and subscription share of revenue.
Use it with repeat purchase rate and LTV to understand whether customer value is leaking after acquisition.
Benchmarks
E-commerce churn benchmark reference points
In ecommerce, churn must be defined carefully. A subscription cancellation is observable. A non-subscription shopper simply not returning within a chosen window is an inferred churn event.
~5–9% monthly
Several 2025/2026 subscription-commerce benchmarks place typical monthly churn in the mid-to-high single digits for ecommerce subscriptions.
10–15% monthly
Subscription box categories can see materially higher churn because novelty declines and failed payments create involuntary churn.
Below 5%
For DTC subscription brands, below 5% monthly churn is commonly treated as a strong retention signal.
| Churn benchmark | Directional range | Interpretation |
|---|---|---|
| Excellent subscription churn | Below 5% monthly | Strong retention, especially for monthly DTC subscriptions. |
| Healthy / typical subscription churn | 5–9% monthly | Common operating range depending on product category and billing cadence. |
| High subscription churn | 10–15% monthly | Often seen in discovery boxes, low-necessity products or weak onboarding. |
| Non-subscription ecommerce churn | Window-dependent | Define churn as no repeat purchase within a category-specific time window. |
Definitions
Subscription churn vs. customer inactivity
| Type | Definition | Best use |
|---|---|---|
| Subscriber churn | Subscribers cancelled or failed to renew during a period | Subscription boxes, replenishment subscriptions and memberships. |
| Voluntary churn | Customer actively cancels | Product-market fit, price, frequency and experience analysis. |
| Involuntary churn | Customer is lost due to failed payment or billing issue | Dunning, payment retries and account updater optimization. |
| Inferred ecommerce churn | Customer did not repurchase within the expected buying window | Non-subscription stores with repeat purchase behavior. |
Segments
Churn patterns by ecommerce category
| Category | Expected churn pattern | Reason |
|---|---|---|
| Supplements, pet food, coffee | Lower churn potential | Replenishment need and routine usage support retention. |
| Meal kits and food delivery | Higher churn risk | Price sensitivity, novelty fatigue and household schedule changes increase cancellations. |
| Beauty subscriptions | Moderate churn | Replenishment can help, but product fit and inventory buildup can trigger cancellation. |
| Discovery boxes | High churn risk | Novelty wears off and perceived value varies month to month. |
| Non-subscription fashion | Window-based churn | Customers may return seasonally rather than monthly. |
Usage
How to use churn benchmarks
Use churn benchmarks to locate retention leakage, but avoid comparing a subscription cancellation rate with a one-time ecommerce repeat-purchase gap. For non-subscription stores, define the expected repurchase window by category before calling a customer churned.
| Use case | Metric to track | Action |
|---|---|---|
| Subscription health | Gross churn, voluntary churn, involuntary churn | Improve onboarding, skip/pause options, billing recovery and lifecycle email. |
| Repeat purchase analysis | No second order within expected window | Build replenishment reminders, post-purchase education and win-back campaigns. |
| Category comparison | Churn by SKU family or cohort | Separate replenishment products from seasonal and discretionary products. |
Methodology
Methodology note
Subscription churn is normally calculated as customers or subscribers lost during a period divided by customers or subscribers at the beginning of the period. Non-subscription ecommerce churn should be calculated using a defined inactivity window, such as no second purchase within 90, 180 or 365 days, depending on category purchase frequency.
Sources
Sources and notes
Use these sources as directional benchmarks. Retention economics should be normalized by category, margin, order frequency, subscription model, attribution window and customer cohort.
Cite this page
How to cite this dataset
E-commerce Churn Rate Benchmarks. Best For Ecommerce. Updated 2026-05-31. Available at: https://bestforecommerce.com/ecommerce-statistics/customer-retention/churn-rate-benchmarks/