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Subscription Decay Calculator

By Herzel MishelFounder, AgentisLast reviewed

Subscription ecommerce (replenishment boxes, vitamins, pet food, coffee) economics looks healthy in the first month. The customer pays full price, COGS is locked at sourcing cost, margin per box is on plan. The challenge starts in months 2-12 when three forces compound: cohort retention attrition (a percentage of subscribers cancel each month), price-locked subscription terms running into rising COGS (you can't reprice an active subscription), and freight cost drift (carrier surcharges, fuel adjustments). The blended effect is what subscription operators call decay: per-cohort margin shrinks meaningfully each month and the aggregate steady-state margin is materially lower than month-1 reporting suggests. This calculator models the 12-month margin trajectory of a single cohort given its retention curve and the rate of COGS drift.

Inputs

subs

How many active subscribers in month 1 of this cohort.

$

Gross margin (revenue minus COGS, freight, payment fees) on a month-1 order.

%

Percentage of active subscribers who cancel each month. Typical DTC subscription: 5-15%.

%

Percentage by which per-order COGS increases each month (supplier price increases, freight surcharges, FX). Typical: 0.5-1.5%.

Results

Month-1 Cohort Profit

$18,000

Month-12 Cohort Profit

$6,585

12-Month Profit Decay

63.4%

Year-1 Total Cohort Profit

$137,249

Month-12 Surviving Subscribers

400 subs

What the Result Means

The decay percentage is the headline metric: typical mid-market subscription DTC sees 60-80% profit decay from month 1 to month 12. A 70% decay means a $1,000 month-1 cohort profit becomes $300 by month 12. The Year-1 Total is the cumulative-cohort-profit metric used for cohort-LTV calculations and CAC-payback decisions. Critically, the steady-state monthly profit (month 12 in this model) is what determines unit economics on the marginal subscriber after the cohort matures. This is the number a CFO uses to size acquisition spend, not the month-1 profit which subsidizes the assumption that all 1,000 subscribers persist forever.

How It's Calculated

The calculator models a single cohort over 12 months. For each month n (n = 1 to 12): surviving subscribers = month-1 subscribers × (1 - churn rate)^(n-1); per-order margin = month-1 margin × (1 - COGS drift rate)^(n-1); cohort profit at month n = surviving subscribers × per-order margin. Year-1 total profit = sum of all 12 monthly cohort profits. Decay percentage = (month-1 profit − month-12 profit) / month-1 profit × 100. The model assumes monthly billing cadence, no acquisition cost amortization (treat that separately), and no upselling or cross-selling within the cohort. Real cohorts have non-uniform churn (early-month churn is typically 2-3× later-month churn), so the constant-churn-rate model is a simplification. For more accurate modeling, run the calculator twice (once with month-1-to-3 churn and once with month-4-to-12 churn) and blend the results.

The Gap This Calculator Reveals

Subscription decay is structural and inevitable but the COGS-drift component can be partially recovered through margin-aware subscription renewal logic. When a subscriber's locked-in price would create a below-floor renewal due to COGS drift, the merchant has options: pause and notify (with a price-update offer), pause and route to retention with a counter-offer, or skip the cycle. Most subscription platforms run renewals as a billing event without margin awareness; the renewal fires regardless of current cost basis, and the loss is realized at the warehouse. A profit firewall integrated with the subscription platform evaluates each renewal against current COGS at billing time and routes below-floor renewals to a retention flow rather than shipping at a loss. Stores running this pattern recover 2-4 percentage points of subscription gross margin annually with no measurable impact on retention, because customers with below-floor lock-ins are the same customers who would have churned at the next sourcing cost spike.

Sources

Frequently Asked Questions

What's a typical monthly churn rate for ecommerce subscriptions?

Replenishment categories (vitamins, pet food, household consumables) typically run 5-10% monthly churn after the early-cohort spike. Discovery boxes (subscription beauty, food curation) typically run 10-18%. The early-cohort spike (months 1-3) is usually 2-3× the steady-state rate as customers test and decide. The calculator's constant-rate assumption underestimates early-cohort churn and overestimates steady-state subscribers; for accuracy, run separate calculations for the spike period and the steady state. In the calculator, the monthly churn rate input drives the surviving subscribers each month, so a small change compounds over 12 months into a large difference in month-12 subscribers and year-1 total cohort profit. The methodology models survivors as month-1 subscribers multiplied by one minus the churn rate raised to the month number minus one. Pull your own cohort retention data by month, fit a rate for the spike period and one for the steady state, and run the calculator with each to get a realistic decay picture for your store.

Does this model upsells, add-ons, or product upgrades?

No. The calculator models a single SKU subscription with a fixed margin per order. If your subscription includes upsells (the customer started at a $30 box and is now on a $50 box), or add-ons (customers buying one-time products on top of subscription), or product upgrades, the per-order margin grows over the cohort lifetime, partially offsetting decay. For those scenarios, model the upsell-adjusted margin separately and add it to the calculator's output. The methodology fixes per-order margin at the month-1 value and reduces it only by the COGS drift rate each month, so any growth in order value is outside the model. A practical approach is to compute the average margin uplift from upsells per surviving subscriber and add it to each month's cohort profit. If expansion revenue is a large part of your economics, track base decay and upsell contribution as two separate numbers for your store.

How do I incorporate this into LTV calculations?

The Year-1 Total Cohort Profit is the year-1 contribution to LTV (before customer acquisition cost). For full LTV, extend the model: project year 2 by applying continued churn to month-12 surviving subscribers, with year-2 COGS drift starting from month-12 levels. Most subscription LTV models use 3-year horizons; beyond that, the cumulative survivor count is small enough that further extension adds noise rather than signal. The calculator's Year-1 Total is the sum of the 12 monthly cohort profits, each computed as surviving subscribers multiplied by per-order margin for that month. To extend into year 2, use the month-12 surviving subscribers output as the new starting cohort and the month-12 per-order margin as the new month-1 margin, then run the model again. Because the model excludes acquisition cost, subtract CAC separately when comparing LTV to spend. Build the multi-year view from these pieces for your store rather than assuming month-1 profit persists.

What if my COGS drift is non-linear (e.g., one-time price hike rather than monthly drift)?

The calculator assumes uniform monthly drift. For one-time hikes, model the period before the hike with 0% drift, the period after with the new (higher) per-order COGS as the month-1 input, and connect the two cohorts manually. The decay framework still applies; uniform drift is just the simpler case. In practice, set the monthly COGS drift input to 0% and run the calculator for the months before the price hike, noting the surviving subscribers at the last month of that period. Then start a second run with those survivors as the month-1 subscribers, the new higher cost reflected in a lower month-1 gross margin per order, and the churn rate continued. Add the cohort profits from both runs to get the year-1 total. The decay percentage across the combined series will show a step down at the hike rather than a smooth slope. This is more work than a single run, but it matches how supplier price increases usually arrive for a subscription store: all at once, at contract renewal.

How does this interact with margin-aware renewal enforcement?

Without margin enforcement, every renewal fires regardless of current cost basis; once a cohort's locked-in price falls below COGS, the subscription becomes unprofitable immediately. With margin enforcement (a profit firewall), below-floor renewals are paused and routed to a retention flow with a price update offer. This effectively floors the margin trajectory: instead of the cohort decaying past zero into negative-margin territory in month 9-12, it terminates the negative-margin subscriptions earlier and either renegotiates them or releases them. The practical impact is 2-4 percentage points of recovered gross margin on the cohort. In the calculator, the effect appears as a floor on the per-order margin: once the drift-adjusted margin would fall below your configured floor, the renewal is no longer shipped at that margin. Compare the calculator's unfloored month-12 cohort profit against the same cohort with below-floor renewals removed to estimate the recovered margin for your store.

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