Cancellations / month
51
Free calculator
Type your active subscribers, monthly churn rate, and price per month. Monthly recurring revenue and subscriber lifetime value update as you type. No email, no gate, nothing leaves this page.
The calculator
The boxes start filled with an illustrative example, not a benchmark. Replace it with your own numbers.
Subscribers currently active and being billed, right now.
The share of active subscribers who cancel in a typical month.
What a subscriber pays each billing cycle, before any discount codes or annual-plan pricing.
Monthly recurring revenue
At 850 subscribers and 6% monthly churn, about 51 people cancel a typical month, and a subscriber sticks around for roughly 16.7 months on average.
MRR = active subscribers × price per month cancellations / month = active subscribers × (churn % / 100) average lifetime = 1 / (churn % / 100), in months subscriber LTV = price per month × average lifetime annual run rate = MRR × 12
This is the standard flat-churn lifetime value formula, not something we invented, and it carries the same simplification everywhere it's used: it assumes churn applies evenly across the whole subscriber base regardless of how long someone has been subscribed.
See it on your own data Real numbers from your Shopify store, not a guess.
This applies one flat monthly churn rate evenly across the whole subscriber base, which assumes every subscriber is equally likely to cancel regardless of how long they've been subscribed. Real subscription cohorts almost never behave that way: they usually lose people fastest in month one or two, then settle into a stickier core that churns much more slowly. Averaging those two very different groups into one flat rate is the same simplification any flat-churn LTV formula makes, not something specific to subscription boxes.
The practical effect is that the "average lifetime" and LTV figures above tend to understate how long your stickiest subscribers actually stay, and overstate how long your newest ones will. A cohort-based churn curve, tracking each signup month separately, is the more accurate version of this calculation; it just needs more data than three numbers.
Questions
There is no universal healthy number. It varies by category, by price point, and by how the box is marketed and sold. Lower-priced, impulse-driven boxes tend to run higher churn than higher-priced, considered ones. Compare your own churn against your own history and your own price point, not a generic benchmark you found online.
Not exactly. MRR is a snapshot run-rate calculated from active subscribers and their price, not necessarily the cash actually collected in a given month. Proration on mid-cycle signups, upgrades, downgrades, refunds, and failed payments can all make actual collected revenue differ from the MRR figure.
Inversely, and directly through the formula above: lower churn means a longer average lifetime, which means a higher lifetime value at the same price. Cutting monthly churn in half roughly doubles the average lifetime and, with it, the LTV.
No, and that's a real distinction it doesn't make. Involuntary churn, a payment failing to process, is often fixable through card-retry logic and dunning emails. Voluntary churn, someone actively deciding to cancel, is a different problem with different fixes. This calculator only takes one blended churn rate and can't tell you which kind you're looking at.
In practice, often very different: a meaningful share of cancellations for many subscription boxes happen right after the first shipment, before a subscriber settles in, and the rate among people who make it past that point is usually lower. This calculator uses one flat rate for the whole base, which is a simplification, not a claim that churn is actually constant over a subscriber's lifetime.
Next
Upstream connects real subscriber and order data from your store to show contribution margin per subscriber, not just a flat blended churn rate applied to everyone. It is the connected version of the calculator above.