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Payout models

Payout models are the structures by which an advertiser compensates an affiliate for the traffic or customers it delivers.

Definition

Payout models are the structures by which an advertiser compensates an affiliate for the traffic or customers it delivers. The main models are RevShare (a percentage of the net revenue referred players generate, paid for the life of the deal), CPA (a fixed sum per qualifying action, usually a first-time deposit that meets minimum size and activity rules), CPL (a fixed sum per qualified lead or registration), CPI (a fixed sum per app install), and hybrid combinations such as a reduced CPA plus a reduced revenue share.

The choice of model determines which party carries the risk that a cohort of players turns out to be worth less than expected.

Under RevShare the affiliate and advertiser are aligned on long-term player value: both earn more if the players retain and spend, and both earn nothing from a player who deposits once and leaves. Under CPA the affiliate is paid the same whether the player becomes a whale or churns immediately, so the advertiser carries the variance and protects itself with qualification rules and clawbacks.

Hybrid splits the difference, giving the affiliate some predictable cash flow and some exposure to upside.

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In context

The right model depends on the affiliate's traffic and cash position. A media buyer with tight unit economics and a need to recycle earnings fast usually prefers CPA, because a fixed, known payout per FTD lets them calculate a maximum acquisition cost and scale against it, and they get paid before the player's true value is known.

An SEO or content affiliate whose traffic is durable and whose players retain well usually prefers RevShare, because they capture the long tail of a good cohort's losses rather than a one-time fee. Programmes often let established affiliates choose while starting new ones on CPA with qualification rules and a hold.

Comparing models requires converting them to a common basis. A $120 CPA and a 35% RevShare are only comparable if you model the referred cohort's actual net losses over time: if the average player loses $500 over their lifetime, 35% RevShare is worth $175, beating the CPA; if they lose $250, it is worth $87.50, and the CPA wins.

This is why affiliates run test cohorts under each model before committing, rather than picking based on the headline number.

Worked example

A programme offers an affiliate three options on the same brand: 30% RevShare, $120 CPA, or a $60 + 15% hybrid. The affiliate runs a 200-FTD test cohort on each.

RevShare pays out $95 per player over 90 days and is still climbing; CPA paid $120 immediately; hybrid paid $60 plus $48 and counting. The affiliate keeps CPA for paid-media scaling and RevShare for its SEO traffic.

Related terms

Frequently asked questions

What does Payout models mean in iGaming?+
Payout models is payout models are the structures by which an advertiser compensates an affiliate for the traffic or customers it delivers. the main models are revshare (a percentage of the net revenue referred player……
How is Payout models calculated?+
The calculation depends on the specific context, but typically involves standard iGaming metrics. See the worked example above for a practical illustration.
Why is Payout models important for affiliates?+
Understanding Payout models is essential for negotiating fair deals, tracking performance accurately, and maximising long-term revenue from iGaming partnerships.
What is a good payout models rate?+
Benchmark rates vary by jurisdiction, product type, and deal structure. Industry averages and competitive ranges are discussed in the definition above.
How does Payout models compare to alternatives?+
See the related terms below for direct comparisons between Payout models and alternative approaches used across the iGaming industry.
Where can I learn more about payout models?+
Browse our full iGaming glossary for 80+ terms, or explore jurisdiction matrix and commission calculator for practical tools.

Browse more iGaming terms in our glossary.

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