Recurring Affiliate Income: Build a Churn Model That Tells the Truth

What a recurring affiliate income churn model actually tells you

A recurring affiliate income churn model is a month-by-month table that starts with new referrals, subtracts cancellations and refunds, and multiplies the surviving customers by your commission rate. It shows whether a recurring program grows steadily or leaks away before you spend time promoting it.

If you have looked at a recurring commission offer and thought the math would be simple, you are not alone. One referral becomes one monthly payment, then another referral, then another. The doubt arrives when you imagine a customer cancelling in month two. What happens to the total then? Does the program still deserve your best content, or are you building on a number that only looks good in the headline?

That is the gap this model fills. It is not a forecast from the vendor and it is not a promise about your future earnings. It is a table you can check with a calculator. You put in the number of new paying referrals you might send each month, a churn rate, and the commission per active referral. The table shows the active base after cancellations, failed payments and refunds.

Stripe's documentation describes subscriptions as moving through lifecycle states from creation to cancellation, with payment retries and status changes handled by the billing system ^[1]. For an affiliate, the important part is that a referral is not a fixed monthly payment. It has a state: active, past_due, unpaid or ended by cancellation. Your model has to reflect that. For the term structure behind the numbers, see our guide to recurring affiliate commissions over 12 months.

The three leaks: cancellations, failed payments and refunds

Most beginner models use one number for churn. That hides the three different leaks.

Cancellation is a choice

A customer can cancel the subscription. Stripe's lifecycle starts at creation and ends at cancellation ^[1]. In your model, a cancelled referral stops producing commission from the next billing cycle. If you use a monthly model, count it in the month the cancellation takes effect, not the month you first hear about it.

Failed payment is a status, not always a cancellation

A payment can fail while the customer still intends to stay. Stripe documents a failed recurring payment event and says the subscription can move to past_due or unpaid while retries happen ^[1]. That matters because the referral may look active in your head but produce no commission while the payment is unresolved. Model it as "delinquent churn" if you want to be precise, or fold it into your churn rate if you only need a rough view.

Refunds are reversals

A refund is different from churn. The customer may cancel and get money back, or a payment may be reversed for another reason. Either way, the commission can be reduced or reversed. Kit's affiliate page, for example, says commissions are held for 31 days to account for refunds ^[2]. That is one program's rule, not an industry standard, but it shows why your gross commission line is not cash.

Different commission structures treat these leaks differently. A revenue-share deal may shrink with a refund; a flat bounty may be reversed entirely. Our explainer on affiliate commission types covers those differences. For payout status, see pending, approved, reversed and paid; a commission can be earned in your model and still not be payable yet.

A simple month-by-month churn model you can copy

You do not need paid software to start. A free spreadsheet with six columns is enough for a first pass. The worked example below is deliberately small so you can check the arithmetic by hand.

Illustrative example only — not a prediction, a typical result or an earnings claim. Assumptions: 10 new paying referrals each month; 8% monthly churn applied to active referrals at the start of the month, rounded to the nearest whole referral; $20 commission per active referral per month; no refunds in this first table.

Formulas:

Active at end = Active at start + New referrals − Churned
Churned = ROUND(8% × Active at start, 0)
Gross commission = Active at end × $20

Month 12 ends with 79 active referrals and $1,580 in gross commission. That is the arithmetic of the assumptions, not a benchmark. If you change the churn rate, the ending number changes. If you add a refund rate, the net number changes again. If the program holds commissions for 31 days, the cash arrives later than the gross line ^[2].

You can copy the columns into a spreadsheet. If you want a pre-built starting point, our affiliate commission calculator is one option; check that its assumptions match the program you are testing.

How to read the result: growth, plateau or leak

The table above is still rising at month 12, but it will not rise forever with fixed new referrals. A simple churn model tends toward a steady state: new referrals per month divided by the monthly churn rate. At 10 new referrals and 8% churn, the rough ceiling is 125 active referrals. The month-12 number is still below that ceiling, which is why it looks healthy.

Change the churn rate and the same 10 new referrals tell a different story. This sensitivity table uses the same assumptions and rounds churn to whole referrals.

The point is not that 4% is good and 20% is bad. The point is that a churn assumption you never checked can change the month-12 number by hundreds of dollars. Use a range: a low case, a base case and a high case. Then ask three questions.

• Is the curve still rising at month 12, or has it flattened?
• How much of month 12 gross commission comes from referrals you expect in the last three months?
• What happens if new referrals stop for three months? Does the base shrink slowly or vanish?

If the curve flattens early, the program is replacing churn with new referrals rather than compounding. That can still be a good program, but it is a different job: you are running on a treadmill, not building a tail. If the curve falls, churn is outrunning new referrals and the headline rate is misleading for your situation.

What to check in a program's terms before you trust the recurring rate

A recurring rate is only one line in the deal. The same word can mean first 12 months, the customer's lifetime, or a lower rate after a threshold. The table below uses Kit's published affiliate page as a worked example. It is not a recommendation and it is not a statement that every program works this way.

Before you join any program, read the actual terms, not just the affiliate landing page. Our checklist of 12 clauses to read in an affiliate program's terms covers the ones that change the math. Also check cookie duration and attribution windows, because a referral that is not credited is a zero in your model no matter how good the commission rate looks.

The 40-month figure is a useful reminder that "recurring" can be longer than a year, but it is one vendor's published average ^[2]. It is not a benchmark for every program, and it is not your expected customer lifetime. Put it in the low, base or high case and label it clearly.

Build the model in a spreadsheet: a fill-in template

Here is a simple layout you can copy into any spreadsheet. The labels are plain on purpose so you can change them without breaking formulas.

Then copy the formulas down. B9 should equal E8. That one link makes the model roll forward. If you change the churn rate in B2, every month updates.

Use the hold column honestly. If the program holds commissions for 31 days, the cash from month 1 may arrive in month 2 ^[2]. That does not change the gross total, but it changes the month you can use the money. If you are comparing two programs, compare both gross and cash timing.

Keep the model boring. Do not add a "viral growth" multiplier unless you can explain where the new referrals come from. Do not add a 40-month average customer life unless the program's current page states it and you label it as the vendor's figure ^[2]. A boring model you can audit is more useful than a polished one you cannot explain.

How to use the model to decide whether to promote a program

The model does not make the decision for you, but it makes the trade-offs visible. Here is a decision table you can use after your month-12 row is filled in.

If the program pays a high first-year rate but a low recurring rate, model the step-down. A 50% first-year commission and a 10% recurring commission are not the same offer, even if both are called recurring ^[2]. If the recurring rate only starts after a threshold you may not reach, use the rate you will actually get, not the headline rate.

Compare payout timing as well as total. Our explainer on CPA vs revenue share shows why a smaller commission paid sooner can be easier to reinvest. If you are judging traffic sources, what EPC means in affiliate marketing helps you avoid comparing your own results with a network average that includes publishers you will never be.

Finally, ask whether the program is worth the maintenance. A recurring commission still needs content, links, disclosure and updates when terms change. If the modelled tail is small after churn, you may be better off with a simpler one-time offer or a different product.

Honest limits: what the model cannot tell you

This model is arithmetic, not evidence that a program will pay you. It cannot predict your referrals, your conversion rate or a vendor's future terms. It cannot tell you whether a customer will cancel because of a price change, a better competitor or a failed card. Those are business questions, not spreadsheet questions.

We are not showing a dashboard screenshot or a test result from a private account, because this article is built from published terms and checkable arithmetic. That is deliberate. Some links on this site may earn a commission; that does not change the arithmetic. If a review tells you one program is best for everyone, ask what churn assumption it used and whether the payout hold and refund rules are included. If it does not show the arithmetic, you cannot audit it.

Payment failure handling differs by payment method and settings ^[1], so your real churn will not be one fixed percentage. Vendor averages, including the 40-month example from Kit's page, are one data point from one program ^[2]. They are not a forecast for your audience. Check the current official page and the date on it before you join; program terms change.

Before you promote anything, run the product through our due-diligence checklist. Then build the model with three scenarios and update it when you have real referral data. The goal is not a perfect forecast. The goal is to avoid being surprised by a number you could have checked.

This guide is general education, not legal, tax or financial advice. Rules and program terms change; check the linked official pages for the current version and ask a qualified professional about your situation. How we write: editorial policy. This page has no affiliate links.