How to Calculate Recurring SaaS Affiliate Income

“How much can I earn?” is a reasonable question about any affiliate programme, but a recurring SaaS offer does not have one honest fixed answer. Income depends on the customers you refer, what they pay, how long they remain eligible, whether attribution is valid, and which programme terms apply. A percentage alone cannot predict the result.

BotMarketing.pro currently provides partners with 30% of a referred customer's payments during the first year and 5% afterwards while that customer remains with the service. The referral must be an end customer of the product, not another seller partner. These percentages describe the commission structure, not guaranteed earnings.

A useful forecast therefore needs three layers: a simple commission formula, a cohort model that reflects retention, and a cash-based check against commission actually received. The examples below use an illustrative monthly customer payment of $100 only to make the arithmetic easy. Replace it with the relevant payment amount and currency, and confirm the current programme rules before making a decision.

The basic first-year commission formula

For a customer during the first twelve months, the simplified formula is:

First-year commission = eligible customer payments × 30%

If one referred customer pays $100 per month and remains active for twelve months:

• monthly eligible payments: $100;
• illustrative monthly commission: $100 × 30% = $30;
• twelve-month commission: $30 × 12 = $360.

This is an idealised full-year example. If the customer pays for only four months, the simplified commission is $100 × 4 × 30% = $120. Registration alone creates no value in this calculation; the model depends on eligible customer payments.

The commission formula after the first year

After the first year, the current rate is 5% while the referred customer continues using and paying for the service:

Later commission = eligible customer payments after year one × 5%

If the same illustrative customer continues paying $100 per month for another twelve months:

• monthly illustrative commission: $100 × 5% = $5;
• second-year commission: $5 × 12 = $60;
• combined two-year commission: $360 + $60 = $420.

The later rate creates a long tail, but it is materially lower than the first-year rate. A forecast should show the two periods separately instead of presenting one blended percentage.

Example with five retained customers

Assume five customers each pay the illustrative $100 per month and all remain active for twelve months:

• eligible monthly payments: 5 × $100 = $500;
• monthly first-year commission: $500 × 30% = $150;
• first-year commission: $150 × 12 = $1,800.

If all five continue for a complete second year:

• monthly later commission: $500 × 5% = $25;
• second-year commission: $25 × 12 = $300;
• illustrative two-year total: $2,100.

This example is useful for understanding the mechanism, not for predicting what five registrations will earn. It assumes identical payments, complete retention, valid attribution, and no interruption.

Example with ten customers and uneven retention

Real cohorts are rarely uniform. Suppose ten customers start at the same illustrative $100 monthly payment:

• four remain for the full twelve months;
• three remain for six months;
• three remain for three months.

The cohort generates 75 customer-months: 4 × 12, plus 3 × 6, plus 3 × 3. Eligible customer payments are therefore 75 × $100 = $7,500. At 30%, the simplified first-year commission is $2,250.

The perfect-retention version of the same ten-customer cohort would produce 120 customer-months, $12,000 in eligible payments, and $3,600 in first-year commission. The $1,350 difference illustrates why registrations or starting customers are not enough to forecast revenue. Retention changes the answer substantially.

Build the forecast around cohorts

A cohort is a group of referred customers who started during the same period or came from the same channel. Cohorts make it easier to compare expected and actual performance.

A basic monthly cohort table can contain:

• qualified referrals;
• attributed registrations;
• customers who made an eligible payment;
• eligible payments by month since acquisition;
• commission accrued or reported;
• commission actually received;
• active customers remaining in each later month.

Do not combine a new cohort at the 30% first-year rate with older customers at the 5% later rate without labelling them. They have different economics and maturity.

Use three scenarios instead of one forecast

A single optimistic number looks precise but hides uncertainty. Build at least three scenarios:

• Downside: fewer paying customers, shorter retention, and slower reporting.
• Base case: assumptions supported by current channel or client data.
• Upside: stronger conversion and retention, clearly labelled as non-guaranteed.

For each scenario, state the assumptions: qualified audience size, referral-to-payment rate, average eligible payment, customer-months in year one, customers reaching year two, and any promotion cost. If an input is unknown, mark it as unknown rather than borrowing an attractive benchmark from an unrelated programme.

Distinguish forecast, accrued commission, and cash received

These numbers answer different questions:

• Forecast commission is a model based on assumptions.
• Reported or accrued commission is what the programme dashboard currently attributes, subject to its rules.
• Received commission is money actually paid to the partner.

Do not count projected future customer payments as current income. Keep a reconciliation by cohort and payment period. Programme reporting and applicable tax records should control the final accounting, not a private spreadsheet estimate.

Calculate customer acquisition cost when promotion is paid

Organic content and existing client relationships still have production costs, but paid campaigns make the calculation more obvious. A simplified acquisition-cost formula is:

Partner acquisition cost per paying customer = total campaign and production cost ÷ new attributed paying customers

Compare this cost with commission actually received, not only the theoretical lifetime commission. For example, spending $600 to acquire six paying customers creates a $100 acquisition cost per customer. If the first months produce only $30 commission per customer, cash payback has not yet occurred. Later commission may improve the result only if customers remain eligible and the attribution continues.

Include landing-page production, creative work, agency fees, software, and the value of substantial staff time where relevant. Ignoring these costs makes a channel look more profitable than it is.

Measure retention quality, not just conversion

A channel can generate many registrations and still produce weak affiliate economics. Compare:

• registration-to-payment rate;
• average eligible payment per paying customer;
• customer-months generated by each cohort;
• percentage of customers still active at useful intervals;
• first-year and later commission received;
• refunds, cancellations, reversals, or rejected attribution where reported;
• common reasons the referred audience was not a fit.

A smaller source with accurate product education may outperform a large source that creates unrealistic expectations. The 30% and 5% structure rewards sustained customer usefulness rather than the click alone.

Model a growing partner base month by month

If new customers arrive regularly, calculate each monthly cohort separately and then add the active cohorts. Do not multiply one successful month indefinitely. A simple model should account for new paying customers, continuing customers, cancellations, changes in eligible payments, and movement from the first-year rate to the later rate.

For example, if a partner adds two suitable paying customers per month, the eligible base can grow, but only while earlier customers remain. The month-six total is not automatically twelve active customers, and the month-twelve total is not automatically twenty-four. Use actual retention as soon as it becomes available and replace assumptions rather than preserving the original forecast.

Questions that materially change the forecast

• Does the partner already reach owners of suitable small businesses?
• Can the product be explained through a specific operational problem?
• How many referrals become eligible paying customers?
• What is the actual distribution of customer payments?
• How long do customers from each channel remain?
• Which costs are required to create and distribute the recommendation?
• What attribution, validation, payout, and eligibility rules currently apply?

Without answers, the model is a sensitivity exercise, not a revenue plan.

Common affiliate income calculation mistakes

• Multiplying the commission rate by registrations instead of eligible payments.
• Assuming every customer remains for twelve months or longer.
• Applying the 30% first-year rate to later years.
• Combining customers at different commission stages without separating cohorts.
• Treating projected commission as money already received.
• Ignoring media, content, implementation, and support costs.
• Using one unusually strong cohort as a permanent baseline.
• Presenting an illustrative calculation as a guaranteed earning claim.

A practical calculation workflow

1. Confirm the current commission, attribution, eligibility, and payout terms.
2. Choose one realistic audience and acquisition channel.
3. Estimate paying customers and customer-months, not clicks alone.
4. Separate first-year commission from the later 5% tail.
5. Build downside, base, and upside scenarios with labelled assumptions.
6. Include all material acquisition and delivery costs.
7. Replace assumptions with cohort data as payments and retention mature.
8. Reconcile the model with commission actually received.

Use the model to improve audience fit

The best calculation is not the one with the largest theoretical total. It is the one that exposes which assumptions matter and helps a partner make better decisions. If weak retention destroys the base case, the answer is usually better qualification and product education, not a more optimistic spreadsheet.

Partners can review the current entry point at BotMarketing.pro seller registration. Before forecasting income, examine the product and current programme terms, then build the model around a realistic source of suitable small-business customers. Treat every example as a planning tool and every payout claim as unproven until programme reporting confirms it.