First-price vs second-price: which bid strategy fits which inventory
The choice is not philosophical. It is mechanical, and it changes how you should set your bids.
1. Second-price auction: the winner pays one cent above the second-highest bid (your bid is a ceiling, not a charge). Optimal strategy is to bid your true value, because you rarely pay it.
2. First-price auction: the winner pays exactly what they bid. Bidding true value now overpays on every win.
3. Today nearly all open exchange supply is first-price after the 2017-2019 transition. But private marketplace deals and some networks still clear second-price, and a few run hybrid.
4. The error: running one flat bid logic across both. On second-price inventory you can bid aggressively to win, paying near the runner-up. Copy that bid into first-price and you pay your full aggressive number every time.
5. When to use each lever — on first-price supply, lean on bid shading (the DSP lowering your bid toward the expected clearing price) and tight pacing. On second-price supply, lean on raw bid value and let the auction mechanic protect you.
Why it matters: the same $4 bid means a $4 cost in first-price and maybe a $1.80 cost in second-price. If your DSP exposes auction type in log-level data, segment win-cost by it before you trust any blended cost figure.
The choice is not philosophical. It is mechanical, and it changes how you should set your bids.
1. Second-price auction: the winner pays one cent above the second-highest bid (your bid is a ceiling, not a charge). Optimal strategy is to bid your true value, because you rarely pay it.
2. First-price auction: the winner pays exactly what they bid. Bidding true value now overpays on every win.
3. Today nearly all open exchange supply is first-price after the 2017-2019 transition. But private marketplace deals and some networks still clear second-price, and a few run hybrid.
4. The error: running one flat bid logic across both. On second-price inventory you can bid aggressively to win, paying near the runner-up. Copy that bid into first-price and you pay your full aggressive number every time.
5. When to use each lever — on first-price supply, lean on bid shading (the DSP lowering your bid toward the expected clearing price) and tight pacing. On second-price supply, lean on raw bid value and let the auction mechanic protect you.
Why it matters: the same $4 bid means a $4 cost in first-price and maybe a $1.80 cost in second-price. If your DSP exposes auction type in log-level data, segment win-cost by it before you trust any blended cost figure.
Supply path optimization: curated marketplaces vs direct SSP integration
Supply path optimization (SPO) is the practice of reducing how many intermediaries sit between your DSP and the publisher. Two tools dominate, and they solve different halves of the problem.
1. Direct SSP integration: you whitelist a short list of SSPs and cut the long tail of resellers. This attacks duplicate auction paths — the same impression offered through five SSPs, where you sometimes bid against yourself.
2. Curated marketplaces (an SSP packaging audience + inventory into a deal): you buy a pre-filtered slice. This attacks quality and targeting, not path count.
3. The tradeoff: direct integration lowers the take rate (the percentage the SSP keeps) because you skip resellers, but it requires you to do the curation yourself. A curated marketplace does curation for you and charges for it — often 8-15% on top.
4. Decide by what is broken. If your log-level data shows the same domain+placement arriving via many seller IDs at different costs, that is a path problem — go direct. If costs are clean but audience is junk, that is a quality problem — buy curation.
Why it matters: people apply curation to a path problem and wonder why fees rose without performance moving. Diagnose path versus quality from seller-ID dispersion in your logs first, then pick the tool.
Supply path optimization (SPO) is the practice of reducing how many intermediaries sit between your DSP and the publisher. Two tools dominate, and they solve different halves of the problem.
1. Direct SSP integration: you whitelist a short list of SSPs and cut the long tail of resellers. This attacks duplicate auction paths — the same impression offered through five SSPs, where you sometimes bid against yourself.
2. Curated marketplaces (an SSP packaging audience + inventory into a deal): you buy a pre-filtered slice. This attacks quality and targeting, not path count.
3. The tradeoff: direct integration lowers the take rate (the percentage the SSP keeps) because you skip resellers, but it requires you to do the curation yourself. A curated marketplace does curation for you and charges for it — often 8-15% on top.
4. Decide by what is broken. If your log-level data shows the same domain+placement arriving via many seller IDs at different costs, that is a path problem — go direct. If costs are clean but audience is junk, that is a quality problem — buy curation.
Why it matters: people apply curation to a path problem and wonder why fees rose without performance moving. Diagnose path versus quality from seller-ID dispersion in your logs first, then pick the tool.
ads.txt vs sellers.json: two files, two questions they answer
Buyers conflate these because both fight spoofing. They verify opposite ends of the chain.
1. ads.txt is published by the publisher. It lists which seller accounts are authorized to sell that domain's inventory. It answers: is this SSP allowed to represent this site at all.
2. sellers.json is published by the SSP/exchange. It maps each seller ID to the actual company behind it, and flags whether they are a PUBLISHER (owns the inventory) or INTERMEDIARY (reselling). It answers: who am I actually buying from, and how many hands has this passed through.
3. SupplyChain object (schain) ties them together in the bid request, listing every node the impression traveled. ads.txt + sellers.json let you validate that chain.
4. When to lean on which — use ads.txt checks to catch domain spoofing (unauthorized sellers claiming a premium domain). Use sellers.json + schain to catch resold inventory and hidden intermediaries inflating your path.
5. A clean ads.txt entry does not mean a short path. The seller can be authorized AND an intermediary. That is the gap most buyers miss.
Why it matters: if you only check ads.txt you stop spoofing but still overpay on long resold paths. If you only read schain you miss the authorization question. Run both against your bid-request logs.
Buyers conflate these because both fight spoofing. They verify opposite ends of the chain.
1. ads.txt is published by the publisher. It lists which seller accounts are authorized to sell that domain's inventory. It answers: is this SSP allowed to represent this site at all.
2. sellers.json is published by the SSP/exchange. It maps each seller ID to the actual company behind it, and flags whether they are a PUBLISHER (owns the inventory) or INTERMEDIARY (reselling). It answers: who am I actually buying from, and how many hands has this passed through.
3. SupplyChain object (schain) ties them together in the bid request, listing every node the impression traveled. ads.txt + sellers.json let you validate that chain.
4. When to lean on which — use ads.txt checks to catch domain spoofing (unauthorized sellers claiming a premium domain). Use sellers.json + schain to catch resold inventory and hidden intermediaries inflating your path.
5. A clean ads.txt entry does not mean a short path. The seller can be authorized AND an intermediary. That is the gap most buyers miss.
Why it matters: if you only check ads.txt you stop spoofing but still overpay on long resold paths. If you only read schain you miss the authorization question. Run both against your bid-request logs.
Forwarded from Иванов и арбитраж трафика
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1. Выкатить ни какую он-лайн конфу я естесвенно не выкатил, потерпите
2. После прошлого видео (тык) мой канал теперь имеет юзер @PO_YICA_BRAL
3. Держите вечернее видео, я нажрусь и спать
Чото надо ещё сказать? Ну, можно лишь добавить Настя #MelBet верни деньги, не играй с огнём, со мной лучше не ссориться. Спасибо.
P.S. Бабка-то, похоже, не своей..... см. видео!
С уважением, Иванов Е.Ю!
2. После прошлого видео (тык) мой канал теперь имеет юзер @PO_YICA_BRAL
3. Держите вечернее видео, я нажрусь и спать
Чото надо ещё сказать? Ну, можно лишь добавить Настя #MelBet верни деньги, не играй с огнём, со мной лучше не ссориться. Спасибо.
P.S. Бабка-то, похоже, не своей..... см. видео!
С уважением, Иванов Е.Ю!
Deal ID vs open auction: when the private path actually pays off
A deal ID is a token in the bid request that unlocks a pre-negotiated arrangement between a buyer and a publisher. It is not automatically better — it is better under specific conditions.
1. Open auction (RTB on the exchange): every buyer competes, you see broad supply, prices float. Cheapest discovery, lowest control.
2. Preferred deal: fixed price, non-guaranteed, you get first look before the open auction. Useful when you want guaranteed access to a segment without committing volume.
3. Private auction (PMP): a closed auction among invited buyers, often with a floor. Useful when the publisher wants competition but only among quality demand.
4. Programmatic guaranteed: fixed price AND fixed volume, no auction at all. This is a reservation booked through pipes.
5. The decision axis is two questions — do you need price certainty, and do you need volume certainty. Open auction gives neither. PG gives both at a premium. Preferred and private sit between.
Why it matters: buyers chase deal IDs for prestige and then find the same impressions cheaper in the open auction, because the deal's floor sits above the clearing price. Before signing, pull the open-auction win-cost for that exact inventory from log-level data. If the deal floor is higher, the deal is costing you, not saving you.
A deal ID is a token in the bid request that unlocks a pre-negotiated arrangement between a buyer and a publisher. It is not automatically better — it is better under specific conditions.
1. Open auction (RTB on the exchange): every buyer competes, you see broad supply, prices float. Cheapest discovery, lowest control.
2. Preferred deal: fixed price, non-guaranteed, you get first look before the open auction. Useful when you want guaranteed access to a segment without committing volume.
3. Private auction (PMP): a closed auction among invited buyers, often with a floor. Useful when the publisher wants competition but only among quality demand.
4. Programmatic guaranteed: fixed price AND fixed volume, no auction at all. This is a reservation booked through pipes.
5. The decision axis is two questions — do you need price certainty, and do you need volume certainty. Open auction gives neither. PG gives both at a premium. Preferred and private sit between.
Why it matters: buyers chase deal IDs for prestige and then find the same impressions cheaper in the open auction, because the deal's floor sits above the clearing price. Before signing, pull the open-auction win-cost for that exact inventory from log-level data. If the deal floor is higher, the deal is costing you, not saving you.
Forwarded from Product Fails | CEO Blask
Пока весь мир смотрел ЧМ, провайдеры делали то, что умеют лучше всего: прикручивали к играм мячи, ворота, футболистов и слово Football.
Мне стало любопытно проверить простую гипотезу: если хайп вокруг ЧМ такой мощный, футбольные игры должны были массово влететь в топы казино.
Не совсем. Хайп — это ещё не билет в топ.
Big Bass Football Bonanza от Pragmatic Play оказался абсолютным монстром дистрибуции: 695 брендов и 626 лобби, почти на 50% впереди ближайшего конкурента.
Но дальше интереснее.
Из глобального топ-10 футбольных тайтлов только 5 слоты. Ещё 4 - instant/casual, один live. Схема «взять слот и нарисовать мяч» d 2026 уже не выглядит такой гениальной.
А деньги при этом были реальные.
У BGaming Soccermania получила: +470% и +308% ставок, а Penalty Duel with Júlio César поднялся со 135-го на 7-е место в категории Crash и вошёл в топ-5 основного лобби.
И вот мой любимый момент: результат сборной вообще не гарантировал результат игре.
Швеция и ЮАР вылетели довольно рано, а их футбольные тайтлы всё равно пробились в локальный топ-20. В Испании, Франции и Аргентине туда вообще вошло сразу по две игры.
Смысл простой: футбольный скин это косметика, а место в топе всё ещё продаётся дистрибуцией и позициями в лобби, не мячиком на обложке.
Больше данных в полном отчёте: https://blask.com/reports/football-titles/
Мне стало любопытно проверить простую гипотезу: если хайп вокруг ЧМ такой мощный, футбольные игры должны были массово влететь в топы казино.
Не совсем. Хайп — это ещё не билет в топ.
Big Bass Football Bonanza от Pragmatic Play оказался абсолютным монстром дистрибуции: 695 брендов и 626 лобби, почти на 50% впереди ближайшего конкурента.
Но дальше интереснее.
Из глобального топ-10 футбольных тайтлов только 5 слоты. Ещё 4 - instant/casual, один live. Схема «взять слот и нарисовать мяч» d 2026 уже не выглядит такой гениальной.
А деньги при этом были реальные.
У BGaming Soccermania получила: +470% и +308% ставок, а Penalty Duel with Júlio César поднялся со 135-го на 7-е место в категории Crash и вошёл в топ-5 основного лобби.
И вот мой любимый момент: результат сборной вообще не гарантировал результат игре.
Швеция и ЮАР вылетели довольно рано, а их футбольные тайтлы всё равно пробились в локальный топ-20. В Испании, Франции и Аргентине туда вообще вошло сразу по две игры.
Смысл простой: футбольный скин это косметика, а место в топе всё ещё продаётся дистрибуцией и позициями в лобби, не мячиком на обложке.
Больше данных в полном отчёте: https://blask.com/reports/football-titles/
Forwarded from Serg Accs
🎁 РОЗЫГРЫШ $2000 ОТ SERG ACCS
🥇 1 место — $1000
🥈 2 место — $700
🥉 3 место — $300
Как участвовать:
1️⃣ Подпишитесь на канал
2️⃣ Нажмите «✅ Участвую»
3️⃣ Получите 1 стартовый билет
Больше билетов:
🛒 Покупки — минимум 1 билет, далее +1 за каждые полные $50 реальной оплаты. Максимум — 50.
👥 Рефералы — +5 за первую подходящую покупку друга и +1 за каждые накопленные $100 его покупок. Максимум — 50.
Общий максимум — 100 билетов.
Чем больше билетов, тем выше шанс. Даже 1 билет участвует.
Призы начислим на баланс в боте SERG ACCS.
Итоги 15.09. Всем удачи! 🔥
🥇 1 место — $1000
🥈 2 место — $700
🥉 3 место — $300
Как участвовать:
1️⃣ Подпишитесь на канал
2️⃣ Нажмите «✅ Участвую»
3️⃣ Получите 1 стартовый билет
Больше билетов:
🛒 Покупки — минимум 1 билет, далее +1 за каждые полные $50 реальной оплаты. Максимум — 50.
👥 Рефералы — +5 за первую подходящую покупку друга и +1 за каждые накопленные $100 его покупок. Максимум — 50.
Общий максимум — 100 билетов.
Чем больше билетов, тем выше шанс. Даже 1 билет участвует.
Призы начислим на баланс в боте SERG ACCS.
Итоги 15.09. Всем удачи! 🔥
Forwarded from AffPapa! Клуб спящих бизнесменов! Потрачено!
Завтра стрим С НАТАШЕЙ ex.ZM где мы обсудим кто как обосрался и был не прав! Типа сплетников но с БАБОЙ! ( у неё пизда ) стрим будет тут https://t.me/+dSPgHo0XFfg4N2U0
Telegram
CPA.TG | JUST NO RESPECT CLUB | МАТАДОРА 🐗
Люди из организации NDA, которых вы можете знать.
Действует правило трёх страйков: если перегрелся, то охлаждаешься на шесть часов. Политика, реклама - сразу на хуй!
🐗 ССЫЛКА https://t.me/+MgUdh-8BhCExYjg0
Действует правило трёх страйков: если перегрелся, то охлаждаешься на шесть часов. Политика, реклама - сразу на хуй!
🐗 ССЫЛКА https://t.me/+MgUdh-8BhCExYjg0
Header bidding vs open bidding (server-side): the latency-vs-control tradeoff
Both are ways for a publisher to let multiple demand sources compete before calling the ad server. The difference is where the auction runs, and it changes what you as a buyer see.
1. Client-side header bidding: the auction runs in the user's browser via a wrapper (Prebid.js is the common one). Each SSP gets a fair, simultaneous call. You see clean, un-deduplicated demand.
2. Server-side / open bidding: the auction runs on a server (Google's Open Bidding, or Prebid Server). Faster page load, but cookie matching degrades because the match happens server-to-server, hurting your user recognition rate.
3. The tradeoff for the buyer: client-side gives better identity resolution (your bid request carries a matched user) but adds browser latency and timeouts that can drop your bid. Server-side is fast but you lose addressability on a meaningful slice of users.
4. How to tell which you are buying through: server-side paths show lower match rates and often a wrapper/exchange node in schain. Client-side shows higher match rates and Prebid signals.
Why it matters: if your audience strategy depends on cookie/ID matching, a publisher's shift to server-side can quietly cut your addressable reach without changing your settings. Watch match-rate by supply path in log-level data — a sudden drop often means the auction moved server-side.
Both are ways for a publisher to let multiple demand sources compete before calling the ad server. The difference is where the auction runs, and it changes what you as a buyer see.
1. Client-side header bidding: the auction runs in the user's browser via a wrapper (Prebid.js is the common one). Each SSP gets a fair, simultaneous call. You see clean, un-deduplicated demand.
2. Server-side / open bidding: the auction runs on a server (Google's Open Bidding, or Prebid Server). Faster page load, but cookie matching degrades because the match happens server-to-server, hurting your user recognition rate.
3. The tradeoff for the buyer: client-side gives better identity resolution (your bid request carries a matched user) but adds browser latency and timeouts that can drop your bid. Server-side is fast but you lose addressability on a meaningful slice of users.
4. How to tell which you are buying through: server-side paths show lower match rates and often a wrapper/exchange node in schain. Client-side shows higher match rates and Prebid signals.
Why it matters: if your audience strategy depends on cookie/ID matching, a publisher's shift to server-side can quietly cut your addressable reach without changing your settings. Watch match-rate by supply path in log-level data — a sudden drop often means the auction moved server-side.
Forwarded from AffPapa! Клуб спящих бизнесменов! Потрачено!
РИДДИК! Первый стрим с Ридиком и Ивановым через пол часа тут https://t.me/+HuSG2ngODc41MjY8 - должен быть разьеб! Иванов пьяный! Сделает красиво!
Bid shading on vs off: when the DSP's discount is working against you
Bid shading is the DSP lowering your submitted bid toward the predicted clearing price in a first-price auction, so you do not overpay. It mimics the old second-price benefit. But it is a model, and models fail at the edges.
1. With shading ON: you bid $4, the algorithm predicts the impression clears at $2.10, it submits ~$2.30. You win and save. This is correct on liquid, high-volume inventory where the prediction has data.
2. With shading ON in thin auctions: on rare, high-value, low-frequency inventory the model has few comparable auctions. It shades on a bad prediction, submits too low, and you lose the impression you most wanted.
3. With shading OFF: you pay full bid every win, but you never lose a must-win impression to a bad shade. Sometimes correct for scarce retargeting pools.
4. The lever most DSPs hide: shading aggressiveness is often a single global setting. The right answer differs by line item — aggressive on broad prospecting, conservative or off on tight retargeting.
Why it matters: a blended win-rate looks fine while your most valuable segment quietly loses auctions to over-shading. Split win-rate by line item and bid-to-clear gap in log-level data. If your highest-value segment has falling win-rate and a wide shade margin, turn shading down there specifically.
Bid shading is the DSP lowering your submitted bid toward the predicted clearing price in a first-price auction, so you do not overpay. It mimics the old second-price benefit. But it is a model, and models fail at the edges.
1. With shading ON: you bid $4, the algorithm predicts the impression clears at $2.10, it submits ~$2.30. You win and save. This is correct on liquid, high-volume inventory where the prediction has data.
2. With shading ON in thin auctions: on rare, high-value, low-frequency inventory the model has few comparable auctions. It shades on a bad prediction, submits too low, and you lose the impression you most wanted.
3. With shading OFF: you pay full bid every win, but you never lose a must-win impression to a bad shade. Sometimes correct for scarce retargeting pools.
4. The lever most DSPs hide: shading aggressiveness is often a single global setting. The right answer differs by line item — aggressive on broad prospecting, conservative or off on tight retargeting.
Why it matters: a blended win-rate looks fine while your most valuable segment quietly loses auctions to over-shading. Split win-rate by line item and bid-to-clear gap in log-level data. If your highest-value segment has falling win-rate and a wide shade margin, turn shading down there specifically.