Cohort Analysis for Affiliate Programmes

Key Takeaways

• Cohort analysis groups your affiliates’ players by the month they arrived and follows that group forward. It does not judge an affiliate on a single month’s total.
• Two affiliates can send you the same number of new depositors in one month and go on to produce very different revenue. A monthly report never shows you which one is which.
• The method runs on data you already collect: which affiliate sent the player, and the deposit or inactivity events that follow. You need no new data source to start.
• PartnerMatrix Affiliate Management and Tracking Software groups and follows these cohorts inside the account you already use to track your programme.

Most affiliate reporting answers one question: how many first-time deposits did this affiliate bring you this month. It is the easiest number to pull. Every dashboard leads with it. It also tells you almost nothing about whether the arrangement is working. A deposit counted on day one says nothing about day ninety, and a monthly total was never built to say more.

Cohort analysis is the correction, and it groups your players by the affiliate who sent them and by the month they arrived, then follows that group forward from the first deposit to the point where it goes quiet, counting every repeat deposit along the way.

We see this most often around a renewal, when a manager pulls the monthly numbers and every affiliate on the list looks roughly the same. Two affiliates can look identical on volume in March and behave nothing alike by June, and a monthly total will not tell you which one is which.

How does cohort analysis help an affiliate programme?

It turns your monthly total into groups you can compare against each other. The method is not ours and it is not new. It comes out of customer analytics rather than this industry, where the case that a business is worth what its customer groups go on to do, rather than how many it signed, has been argued at length by the researchers who value whole companies that way.

Inside iGaming it already appears as one of the standard retention measures, and the affiliate programme is simply where it is least often applied. You can see which affiliates keep producing value after the first deposit, and which ones stop mattering the moment a sign-up bonus clears.

That difference sits underneath every commission decision you make. A total never shows it.

Say two of your affiliates each sent forty new depositors in March. Read only the March total and they look identical: same commission rate, same line in your report.

Follow both groups forward and the picture changes. One affiliate’s March cohort is still mostly active in June, while the other has thinned to almost nothing by the same date.

The traffic behind the second affiliate was a short-lived promotion rather than a source that keeps sending players who stay, and volume alone never shows it.

Illustrative numbers, chosen to show the shape of the difference. Not a measured result.

Same acquisition month, same starting count; nothing in a single month’s report would have told you these two affiliates were heading in opposite directions. That gap decides whether you renew a deal at the same rate or reopen it for renegotiation, and a manager who only reads the monthly total finds out which affiliate was which a quarter too late.

How do you use cohort analysis on an affiliate programme?

Start from data you likely already collect, the affiliate who sent the player and the deposit or inactivity events tied to them since they registered, because none of that calls for a new source, only a different way of grouping what is already on hand.

Group by acquisition period first, then by affiliate. A month is the usual grain, because it lines up with how you already report commission periods and campaign pushes, and it rarely forces you to wait a full quarter before a shape in the data is visible.

A shorter window fits a fast-moving promotion; a longer one suits a programme with slower deposit cycles.

Whichever you choose, follow each group forward the same way every time, from the first deposit through repeat deposits to the point where the group goes quiet. Holding that window steady across affiliates matters more than which exact window you pick, because the method’s value is in setting one cohort against another, which is the whole point of running it.

Then read the comparison, not the count. An affiliate whose cohorts hold up month after month is worth keeping even at a higher rate, because the traffic behind it keeps paying you back.

An affiliate whose cohorts fall away fast is worth a conversation about where that traffic really comes from, whatever last month’s total said.

That conversation belongs with the commission terms themselves, because the deal type decides who carries the risk when a cohort underperforms, and it runs on the same reporting as real-time affiliate data you are already collecting. How iGaming affiliates get paid is the mechanics it feeds into once you get there.

Run it on a fixed schedule, not as a once-a-year audit before a renewal. A cohort only tells you something once enough time has passed for the group to develop.

Checking last quarter’s cohorts against the quarter before, on a set date, is the habit worth keeping, the same date every time so the comparison holds.

Cohort Analysis inside PartnerMatrix Affiliate Management and Tracking Software

This is a native module in PartnerMatrix Affiliate Management and Tracking Software, the back-office software you already use to build and track your programme, so the method above runs on the affiliate and deposit data that account already holds. For each group it surfaces first-time deposits and churn across the life of the group, not only at the moment they first happen.

Volume was never the question worth answering on its own.

That is a different question from the one player segmentation answers inside the same software. Segmentation sets your commission rate by geo, registration period or traffic source, before a player has done anything.

Cohort Analysis reads what a group of players did after they arrived. Treating the two as interchangeable is a mistake this category has already made once.

Common questions about cohort analysis in affiliate marketing

Is cohort analysis the same as player segmentation?

No. Segmentation sets your commission rate in advance, based on geo, registration period or traffic source. Cohort analysis looks back at what a group of players already did after they arrived, which is a different question answered from different data.

How often should you run it?

On a fixed schedule tied to how your commission periods and renewals already work, usually monthly, rather than as a one-off exercise before a renegotiation, because a cohort only tells you something once enough time has passed for the group to develop, and checking it on a set date is what turns it into a warning rather than an after-the-fact explanation.

Does cohort analysis replace FTD reporting?

No, it sits alongside it. An FTD count still answers how many players an affiliate brought you in a given period, while cohort analysis answers what happened to that group afterwards, the half of the story a deposit count was never built to tell.

Can you do cohort analysis without dedicated software?

Yes. A spreadsheet and the fields most tracking systems already export will do it: which affiliate sent the player, and the deposit or inactivity events tied to them since. It gets harder to sustain as a habit once your programme runs more than a handful of affiliates, which is where doing it inside the software already tracking that data starts to matter.

It gives you a pattern to look at before you make the call, not a substitute for your own judgement about the deal. A total looks fine right up until the point it is not; the question that follows is what to do about an affiliate whose cohorts are already thinning, a conversation about the deal type as much as it is about the rate.

Book a demo to see how Cohort Analysis works.