A shave happens when an affiliate network or advertiser quietly cuts part of your leads so they pay less. In short, you do the work, but don’t get fully paid.

Why it happens: to save on payouts, or sometimes just shady behavior, especially from new or unreliable networks. The percentage might be small, but recurring—and you might not notice immediately.

Common Shave Schemes

Regular lead cutting
The network systematically “shaves” a portion of your leads. You might think approvals dropped randomly, but you’re simply being underpaid.

Post-approval reductions
A lead is initially approved, but later the advertiser reduces the payout claiming “low-quality traffic.” Even if your traffic is fine, this is a classic shave.

One-sided offer changes
Sometimes networks change terms—raise thresholds, lower payouts, extend hold periods. If it’s done without explanation, that counts as a shave.

Who Does the Shaving

• Affiliate networks directly cutting payouts.
• Advertisers via middlemen, also trimming leads.
• Most often, it’s young or shady networks that don’t care about reputation.

How to Spot a Shave

• Make a test lead via VPN/proxy and see if it’s counted.
• Compare approval rates across offers—if one is consistently lower, it may be a shave.
• Use trackers to have your own data and not rely solely on the network.

How to Detect a Shave Before Working

• Check reviews from other affiliates—if a network shaves leads, it usually comes up.
• Work with top platforms that value their reputation.

When a Shave Might Be Unintentional

• Technical glitches or approval delays.
• Problems on the advertiser’s side.
• Always verify your traffic quality and landing pages before blaming the network.

Connection to Cookie Stuffing

Cookie stuffing is when cookies are manipulated so payouts go elsewhere. Not exactly a shave, but it also affects stats and revenue.

How to Minimize Shave Risk

• Run test leads.
• Use trusted trackers.
• Monitor reviews and community chats.
• Diversify traffic across multiple networks—this makes anomalies easier to spot.

A shave happens when an affiliate network or advertiser quietly cuts part of your leads so they pay less. In short, you do the work, but don’t get fully paid.

Why it happens: to save on payouts, or sometimes just shady behavior, especially from new or unreliable networks. The percentage might be small, but recurring—and you might not notice immediately.

Common Shave Schemes

Regular lead cutting
The network systematically “shaves” a portion of your leads. You might think approvals dropped randomly, but you’re simply being underpaid.

Post-approval reductions
A lead is initially approved, but later the advertiser reduces the payout claiming “low-quality traffic.” Even if your traffic is fine, this is a classic shave.

One-sided offer changes
Sometimes networks change terms—raise thresholds, lower payouts, extend hold periods. If it’s done without explanation, that counts as a shave.

Who Does the Shaving

• Affiliate networks directly cutting payouts.
• Advertisers via middlemen, also trimming leads.
• Most often, it’s young or shady networks that don’t care about reputation.

How to Spot a Shave

• Make a test lead via VPN/proxy and see if it’s counted.
• Compare approval rates across offers—if one is consistently lower, it may be a shave.
• Use trackers to have your own data and not rely solely on the network.

How to Detect a Shave Before Working

• Check reviews from other affiliates—if a network shaves leads, it usually comes up.
• Work with top platforms that value their reputation.

When a Shave Might Be Unintentional

• Technical glitches or approval delays.
• Problems on the advertiser’s side.
• Always verify your traffic quality and landing pages before blaming the network.

Connection to Cookie Stuffing

Cookie stuffing is when cookies are manipulated so payouts go elsewhere. Not exactly a shave, but it also affects stats and revenue.

How to Minimize Shave Risk

• Run test leads.
• Use trusted trackers.
• Monitor reviews and community chats.
• Diversify traffic across multiple networks—this makes anomalies easier to spot.