Median minimum payout is $100
Minimum payout = balance required before a withdrawal releases. Coded from 44 networks.
— $50 or under: 27%
— $51–$100: 39%
— $101–$250: 23%
— $250+: 11%
≤$50 ▇▇▇▇▇
$51-100 ▇▇▇▇▇▇▇
$101-250 ▇▇▇▇
$250+ ▇▇
For a tester running $300/day, even a $250 threshold clears inside two days; it bites mainly on low-volume or new accounts where it can trap a balance for weeks (n=44).
Read: thresholds matter at low volume, are noise at scale.
Minimum payout = balance required before a withdrawal releases. Coded from 44 networks.
— $50 or under: 27%
— $51–$100: 39%
— $101–$250: 23%
— $250+: 11%
≤$50 ▇▇▇▇▇
$51-100 ▇▇▇▇▇▇▇
$101-250 ▇▇▇▇
$250+ ▇▇
For a tester running $300/day, even a $250 threshold clears inside two days; it bites mainly on low-volume or new accounts where it can trap a balance for weeks (n=44).
Read: thresholds matter at low volume, are noise at scale.
Tier-1 payouts run 4.3x tier-3 for the same action
Geo tier = advertiser grouping by market value (T1 = US/UK/CA/AU, T3 = most of SEA/LATAM).
— Tier-1: index 100 ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
— Tier-2: index 47 ▇▇▇▇▇▇▇▇▇
— Tier-3: index 23 ▇▇▇▇▇
Measured on identical CPA actions across 17 offers. Tier-3 makes up the gap only when traffic cost falls faster than payout, which it usually does not (n=17 offers).
Read: cheap tier-3 traffic still needs a 4x conversion edge to match tier-1 economics.
n=17 offers
Geo tier = advertiser grouping by market value (T1 = US/UK/CA/AU, T3 = most of SEA/LATAM).
— Tier-1: index 100 ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
— Tier-2: index 47 ▇▇▇▇▇▇▇▇▇
— Tier-3: index 23 ▇▇▇▇▇
Measured on identical CPA actions across 17 offers. Tier-3 makes up the gap only when traffic cost falls faster than payout, which it usually does not (n=17 offers).
Read: cheap tier-3 traffic still needs a 4x conversion edge to match tier-1 economics.
n=17 offers
43% of payment failures occur on the first cycle
Failure = late, partial, or non-payment. Coded from 61 reported incidents across affiliate forums, 18-month window.
— Cycle 1: 43% ▇▇▇▇▇▇▇▇▇
— Cycle 2: 19% ▇▇▇▇
— Cycle 3+: 38% ▇▇▇▇▇▇▇▇
First-cycle clustering reflects new-account fraud holds and untested terms, not necessarily a bad network. Survivors past cycle 2 had a 91% on-time rate thereafter (n=61 incidents).
Read: cap exposure on cycle 1, then scale on demonstrated payment history.
Failure = late, partial, or non-payment. Coded from 61 reported incidents across affiliate forums, 18-month window.
— Cycle 1: 43% ▇▇▇▇▇▇▇▇▇
— Cycle 2: 19% ▇▇▇▇
— Cycle 3+: 38% ▇▇▇▇▇▇▇▇
First-cycle clustering reflects new-account fraud holds and untested terms, not necessarily a bad network. Survivors past cycle 2 had a 91% on-time rate thereafter (n=61 incidents).
Read: cap exposure on cycle 1, then scale on demonstrated payment history.
Median dispute closes in 6 business days
Resolution time = ticket open to final ruling on a contested conversion or payment.
— P25: 2 days ▇▇
— Median: 6 days ▇▇▇▇▇▇
— P75: 14 days ▇▇▇▇▇▇▇▇▇▇▇▇▇▇
— P90: 29 days ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
The long tail correlates with broker-model networks that must relay disputes to the advertiser (n=26). Direct-advertiser networks cluster under the median.
Read: resolution speed is a proxy for how many parties sit between you and the money.
n=26 networks
Resolution time = ticket open to final ruling on a contested conversion or payment.
— P25: 2 days ▇▇
— Median: 6 days ▇▇▇▇▇▇
— P75: 14 days ▇▇▇▇▇▇▇▇▇▇▇▇▇▇
— P90: 29 days ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇
The long tail correlates with broker-model networks that must relay disputes to the advertiser (n=26). Direct-advertiser networks cluster under the median.
Read: resolution speed is a proxy for how many parties sit between you and the money.
n=26 networks
Volume payout bumps median at +12%
Payout bump = rate increase granted after sustained volume, vs. public rate card.
— Granted bump: median +12%, range +5% to +35%
— Volume trigger: median 50 conversions/day for 7 days
— Request-to-grant time: median 4 days
In the sample, 22 of 29 affiliates who asked received a bump; the 7 who did not were under the volume trigger (n=29). Asking below threshold has a near-zero hit rate.
Read: hit the volume trigger first, then ask; the bump is almost always there for the asking.
Payout bump = rate increase granted after sustained volume, vs. public rate card.
— Granted bump: median +12%, range +5% to +35%
— Volume trigger: median 50 conversions/day for 7 days
— Request-to-grant time: median 4 days
In the sample, 22 of 29 affiliates who asked received a bump; the 7 who did not were under the volume trigger (n=29). Asking below threshold has a near-zero hit rate.
Read: hit the volume trigger first, then ask; the bump is almost always there for the asking.
EPC variance is 3.1x wider in finance than in sweepstakes
EPC = earnings per click, gross revenue divided by raw clicks sent.
— Sweeps: $0.18 median, coefficient of variation 0.34 ▏▏▏
— Nutra: $0.31, CV 0.52 ▏▏▏▏▏
— Dating: $0.44, CV 0.61 ▏▏▏▏▏▏
— Finance/loans: $0.92, CV 1.06 ▏▏▏▏▏▏▏▏▏▏▏▏
CV = standard deviation / mean; higher CV means EPC is less predictable per click. Finance pays more per click but the spread is so wide that small samples mislead. n=measured across ~2,900 campaigns.
Read: in high-CV verticals, judge an offer on 1,000+ clicks minimum before trusting its EPC.
EPC = earnings per click, gross revenue divided by raw clicks sent.
— Sweeps: $0.18 median, coefficient of variation 0.34 ▏▏▏
— Nutra: $0.31, CV 0.52 ▏▏▏▏▏
— Dating: $0.44, CV 0.61 ▏▏▏▏▏▏
— Finance/loans: $0.92, CV 1.06 ▏▏▏▏▏▏▏▏▏▏▏▏
CV = standard deviation / mean; higher CV means EPC is less predictable per click. Finance pays more per click but the spread is so wide that small samples mislead. n=measured across ~2,900 campaigns.
Read: in high-CV verticals, judge an offer on 1,000+ clicks minimum before trusting its EPC.
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For Native ads done right, @NativeHeresy is the move. We torch native-ads myths: when 'premium placements' lie, why your CTR is fake, and…
For Native ads done right, @NativeHeresy is the move. We torch native-ads myths: when 'premium placements' lie, why your CTR is fake, and…
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Net-7 is now the modal payment term, but only 38% of networks honor it on schedule
Net-X = days after period close until you actually get paid.
— Net-7 advertised: 41% of networks ▏▏▏▏▏▏▏▏
— Net-7 paid on time (within 2 days): 38% of advertised ▏▏▏▏
— Weekly: 27% ▏▏▏▏▏
— Net-15: 21% ▏▏▏▏
— Net-30: 11% ▏▏
Advertised frequency and realized frequency diverge most at Net-7; the faster the promise, the larger the slippage. n=46 networks, 9-month payment-log sample.
Read: weight a network's payment term by its on-time rate before treating speed as a perk.
Net-X = days after period close until you actually get paid.
— Net-7 advertised: 41% of networks ▏▏▏▏▏▏▏▏
— Net-7 paid on time (within 2 days): 38% of advertised ▏▏▏▏
— Weekly: 27% ▏▏▏▏▏
— Net-15: 21% ▏▏▏▏
— Net-30: 11% ▏▏
Advertised frequency and realized frequency diverge most at Net-7; the faster the promise, the larger the slippage. n=46 networks, 9-month payment-log sample.
Read: weight a network's payment term by its on-time rate before treating speed as a perk.
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Алиса AI будет конкурировать с Google AI Studio
Яндекс разворачивает экосистему AI-агентов на базе Алисы с доступом сначала для компаний, затем для всех. Агенты уже работают в Яндекс Такси и Лавке, скоро появятся в браузере и студии разработки. Платформа интегрирует стандартные функции — заказ такси, покупки, анализ данных. Алиса AI показывает неплохие результаты: менее известна, чем конкуренты, поэтому предлагает щедрые лимиты на видеогенерацию и работу с контентом. Яндекс планирует внедрить…
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Яндекс разворачивает экосистему AI-агентов на базе Алисы с доступом сначала для компаний, затем для всех. Агенты уже работают в Яндекс Такси и Лавке, скоро появятся в браузере и студии разработки. Платформа интегрирует стандартные функции — заказ такси, покупки, анализ данных. Алиса AI показывает неплохие результаты: менее известна, чем конкуренты, поэтому предлагает щедрые лимиты на видеогенерацию и работу с контентом. Яндекс планирует внедрить…
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