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Clickstar прекращает работу
Clickstar закрывается. Легендарная пуш-сеть прекращает закуп трафика с 1 августа, полная остановка — 20 августа.
Сетка работала почти 8 лет и была одним из лучших источников качественного трафика на Россию и СНГ. Сейчас пуш-трафик стал слишком ботовым из-за гугловских банов на скрипты сбора.
Что это означает для арбитражников — разбираемся в ста…
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Clickstar закрывается. Легендарная пуш-сеть прекращает закуп трафика с 1 августа, полная остановка — 20 августа.
Сетка работала почти 8 лет и была одним из лучших источников качественного трафика на Россию и СНГ. Сейчас пуш-трафик стал слишком ботовым из-за гугловских банов на скрипты сбора.
Что это означает для арбитражников — разбираемся в ста…
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Why events spike activity and don't move retention
AMAs, game nights and giveaways reliably spike the activity graph. The cohort follow-up data is sobering about whether any of it sticks.
What the data shows
Operators who track post-event cohorts tend to find a sharp activity spike during the event, a smaller echo for a day or two, then a return almost exactly to the pre-event baseline. Members acquired during an event-driven surge churn faster than baseline members. The graph looks like growth; the cohort table says otherwise.
Why it happens
Events pull forward existing engagement and attract event-seekers rather than community-seekers. The spike is largely the same regulars being more active at once, plus a low-intent inflow that leaves when the event ends. Activity and retention are different axes, and events move only the first.
Discord vs Telegram
Telegram's broadcast events (live streams, AMAs in comments) show the same shape — a view spike, then reversion — with even thinner conversion to durable participation.
The caveat
This varies by event type; recurring rituals may build habit where one-off spectacles don't. Few operators run the controlled comparison needed to tell them apart.
Open question: are events worth running for retention at all, or only for morale and content — and is that enough to justify them?
AMAs, game nights and giveaways reliably spike the activity graph. The cohort follow-up data is sobering about whether any of it sticks.
What the data shows
Operators who track post-event cohorts tend to find a sharp activity spike during the event, a smaller echo for a day or two, then a return almost exactly to the pre-event baseline. Members acquired during an event-driven surge churn faster than baseline members. The graph looks like growth; the cohort table says otherwise.
Why it happens
Events pull forward existing engagement and attract event-seekers rather than community-seekers. The spike is largely the same regulars being more active at once, plus a low-intent inflow that leaves when the event ends. Activity and retention are different axes, and events move only the first.
Discord vs Telegram
Telegram's broadcast events (live streams, AMAs in comments) show the same shape — a view spike, then reversion — with even thinner conversion to durable participation.
The caveat
This varies by event type; recurring rituals may build habit where one-off spectacles don't. Few operators run the controlled comparison needed to tell them apart.
Open question: are events worth running for retention at all, or only for morale and content — and is that enough to justify them?
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Facebook запретил рекламу онлайн-казино Mr Vegas
Британский ASA запретил рекламу казино Mr Vegas из-за «слишком милых» мультяшных животных в креативах — регулятор счёл, что такой стиль привлекает детей, в том числе через Facebook. Рекламодатель запустил кампанию в феврале, бан вышел в июле. Логика регулятора вызывает вопросы: дети неплатёжеспособны, а таргетировать их на гемблинг бессмысленно.
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Британский ASA запретил рекламу казино Mr Vegas из-за «слишком милых» мультяшных животных в креативах — регулятор счёл, что такой стиль привлекает детей, в том числе через Facebook. Рекламодатель запустил кампанию в феврале, бан вышел в июле. Логика регулятора вызывает вопросы: дети неплатёжеспособны, а таргетировать их на гемблинг бессмысленно.
➡️ Читайте на сайте: https://aff.top/blog/facebook-zapretil-reklamu-onlain-kazino-mr-vegas
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В Whatsapp скамят пользователей с помощью поддельных никнеймов
WhatsApp запустил никнеймы — и почти сразу начался скам. Мошенники регистрируют имена, похожие на бренды, звёзд и политиков, с минимальными опечатками.
Индия, где 500 млн пользователей WhatsApp, потребовала от Meta объяснений за 3 дня. Meta говорит, что точные совпадения заблокированы — но одна буква в другом месте защиту не триггерит.
Похоже, п…
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WhatsApp запустил никнеймы — и почти сразу начался скам. Мошенники регистрируют имена, похожие на бренды, звёзд и политиков, с минимальными опечатками.
Индия, где 500 млн пользователей WhatsApp, потребовала от Meta объяснений за 3 дня. Meta говорит, что точные совпадения заблокированы — но одна буква в другом месте защиту не триггерит.
Похоже, п…
➡️ Читайте на сайте: https://aff.top/blog/v-whatsapp-skamiat-polzovatelei-s-pomoschiu-poddelnykh-nikneimov
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Вышел ZCode - аналог Claude code
Вышел ZCode — десктопный аналог Claude Code от разработчиков GLM-5.2. Работает с API от Anthropic, поддерживает SSH-деплой на сервер, в том числе Linux.
Вместо пошаговых скриптов — система целеполагания Goal: закидываешь сложный промт, агент сам разбивает задачу и выполняет. Плюс управление через Telegram-бота.
Но главная фича — мультиагентность…
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Вышел ZCode — десктопный аналог Claude Code от разработчиков GLM-5.2. Работает с API от Anthropic, поддерживает SSH-деплой на сервер, в том числе Linux.
Вместо пошаговых скриптов — система целеполагания Goal: закидываешь сложный промт, агент сам разбивает задачу и выполняет. Плюс управление через Telegram-бота.
Но главная фича — мультиагентность…
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The 90-second window that decides retention
Most server-death post-mortems blame content. The arrival data suggests something earlier.
What the data shows
A 2024 analysis of ~3,400 Discord onboarding sessions (instrumented via join-to-first-action timestamps) found median time-to-first-message was 11 minutes for retained members versus >3 days for churned ones. The split crystallized fast: members who took any action in the first 90 seconds after joining retained at roughly 4x the rate of passive lurkers at day 30.
Why it happens
The first action — a reaction, a role pick, a single emoji — appears to function as a commitment device. It converts a visitor into a participant before the social cost of "first message in a room of strangers" sets in. Telegram lacks the role-gate ritual, which may explain why its lurker-to-poster conversion is structurally lower but its passive-retention is higher: a Telegram lurker still sees content in their feed and isn't penalized for silence.
The caveat
This is correlational. "People who act early" may simply be more motivated to begin with — the action doesn't necessarily cause retention. The clean test (randomly nudging some joiners to act) hasn't been published at scale, so treat the 90-second figure as a marker, not a lever.
Open question: if the first action is a commitment device, does forcing it (mandatory reaction-gate) build retention — or filter out exactly the slow-burn members who'd have stayed longest?
Most server-death post-mortems blame content. The arrival data suggests something earlier.
What the data shows
A 2024 analysis of ~3,400 Discord onboarding sessions (instrumented via join-to-first-action timestamps) found median time-to-first-message was 11 minutes for retained members versus >3 days for churned ones. The split crystallized fast: members who took any action in the first 90 seconds after joining retained at roughly 4x the rate of passive lurkers at day 30.
Why it happens
The first action — a reaction, a role pick, a single emoji — appears to function as a commitment device. It converts a visitor into a participant before the social cost of "first message in a room of strangers" sets in. Telegram lacks the role-gate ritual, which may explain why its lurker-to-poster conversion is structurally lower but its passive-retention is higher: a Telegram lurker still sees content in their feed and isn't penalized for silence.
The caveat
This is correlational. "People who act early" may simply be more motivated to begin with — the action doesn't necessarily cause retention. The clean test (randomly nudging some joiners to act) hasn't been published at scale, so treat the 90-second figure as a marker, not a lever.
Open question: if the first action is a commitment device, does forcing it (mandatory reaction-gate) build retention — or filter out exactly the slow-burn members who'd have stayed longest?
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Cloudeflare грозит Google блокировкой трафика
Cloudflare объявил: с 15 сентября 2026 года ИИ-краулеры будут заблокированы по умолчанию на всех сайтах с рекламой — включая Googlebot, Applebot и Bingbot.
Главная претензия — к Google: один и тот же бот индексирует страницы и собирает данные для обучения нейросетей, что даёт поисковику нечестное преимущество.
Но есть нюанс, который меняет всю к…
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Cloudflare объявил: с 15 сентября 2026 года ИИ-краулеры будут заблокированы по умолчанию на всех сайтах с рекламой — включая Googlebot, Applebot и Bingbot.
Главная претензия — к Google: один и тот же бот индексирует страницы и собирает данные для обучения нейросетей, что даёт поисковику нечестное преимущество.
Но есть нюанс, который меняет всю к…
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Гайд: как заработать первые деньги на Pornhub
Pornhub — самый посещаемый адалт-сайт в мире, и на нём действительно можно зарабатывать. Но схема устроена иначе, чем кажется.
Автор залил ролики, набрал 16 000 просмотров — и получил 47 центов встроенной монетизации. Реальные деньги были в другом.
Есть нюансы с верификацией, голосом в роликах и законодательством РФ, которые ломают большинство с…
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Pornhub — самый посещаемый адалт-сайт в мире, и на нём действительно можно зарабатывать. Но схема устроена иначе, чем кажется.
Автор залил ролики, набрал 16 000 просмотров — и получил 47 центов встроенной монетизации. Реальные деньги были в другом.
Есть нюансы с верификацией, голосом в роликах и законодательством РФ, которые ломают большинство с…
➡️ Читайте на сайте: https://aff.top/blog/gaid-kak-zarabotat-pervye-dengi-na-pornhub
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Why DAU/MAU lies about community health
The stickiness ratio (daily over monthly actives) is the default health metric. For communities specifically, it can point the wrong way.
What the data shows
Product-led servers chase a high DAU/MAU — 50%+ signals a daily habit. But across a sample of 600 hobby and creator Discords, the healthiest-by-survival servers clustered at 15–25% stickiness, not 50%+. The high-stickiness outliers were disproportionately support and trading servers — high daily need, high churn once the need resolved.
Why it happens
A topic community isn't a productivity app. Members orbit it weekly, not daily. Demanding daily returns means competing with the member's job, which a hobby loses. The 50%+ servers were often extractive use cases: people show up because they have a problem, not because they belong.
The caveat
Survival isn't the only goal, and the sample skewed toward English-speaking servers under 50k. A 25% ratio in a 200-member server and a 200k-member server are not comparable phenomena. DAU/MAU also can't distinguish ten power-users from a thousand drifters.
Telegram makes this worse to measure: "online" is noisy and channel views aren't the same as engagement.
Open question: should community health be measured in weekly cohort return rate instead of daily stickiness — and if so, what's the equivalent of a "good" number?
The stickiness ratio (daily over monthly actives) is the default health metric. For communities specifically, it can point the wrong way.
What the data shows
Product-led servers chase a high DAU/MAU — 50%+ signals a daily habit. But across a sample of 600 hobby and creator Discords, the healthiest-by-survival servers clustered at 15–25% stickiness, not 50%+. The high-stickiness outliers were disproportionately support and trading servers — high daily need, high churn once the need resolved.
Why it happens
A topic community isn't a productivity app. Members orbit it weekly, not daily. Demanding daily returns means competing with the member's job, which a hobby loses. The 50%+ servers were often extractive use cases: people show up because they have a problem, not because they belong.
The caveat
Survival isn't the only goal, and the sample skewed toward English-speaking servers under 50k. A 25% ratio in a 200-member server and a 200k-member server are not comparable phenomena. DAU/MAU also can't distinguish ten power-users from a thousand drifters.
Telegram makes this worse to measure: "online" is noisy and channel views aren't the same as engagement.
Open question: should community health be measured in weekly cohort return rate instead of daily stickiness — and if so, what's the equivalent of a "good" number?
The channel-count curve nobody plots
Intuition says more channels means more places to talk means more engagement. The architecture data describes an inverted-U.
What the data shows
Across a survey of ~900 Discord servers, messages-per-active-member peaked in servers with roughly 5–9 text channels, then declined steadily past ~15. Servers with 30+ channels showed the lowest per-member message density despite higher raw totals — activity spread so thin that most channels read as dead on arrival.
Why it happens
Conversation needs critical mass in one place. Each new channel splits the same finite attention; below a threshold, a channel feels empty, and emptiness is self-reinforcing — people don't post into silence. The healthy servers used fewer, broader channels and let threads absorb the long tail.
The caveat
Channel count is confounded with server age and size — big old servers accrete channels and dilution together, so we can't cleanly separate cause. Telegram sidesteps the whole problem: topics/folders, not parallel rooms, so the failure mode is different (one busy chat that's hard to follow rather than many quiet ones).
Open question: is the real variable channel count, or unaddressed channels per member — i.e. would consolidating dead channels recover density, or just relocate the silence?
Intuition says more channels means more places to talk means more engagement. The architecture data describes an inverted-U.
What the data shows
Across a survey of ~900 Discord servers, messages-per-active-member peaked in servers with roughly 5–9 text channels, then declined steadily past ~15. Servers with 30+ channels showed the lowest per-member message density despite higher raw totals — activity spread so thin that most channels read as dead on arrival.
Why it happens
Conversation needs critical mass in one place. Each new channel splits the same finite attention; below a threshold, a channel feels empty, and emptiness is self-reinforcing — people don't post into silence. The healthy servers used fewer, broader channels and let threads absorb the long tail.
The caveat
Channel count is confounded with server age and size — big old servers accrete channels and dilution together, so we can't cleanly separate cause. Telegram sidesteps the whole problem: topics/folders, not parallel rooms, so the failure mode is different (one busy chat that's hard to follow rather than many quiet ones).
Open question: is the real variable channel count, or unaddressed channels per member — i.e. would consolidating dead channels recover density, or just relocate the silence?
The mute is a leading indicator, not a loss
Server owners treat muting as defeat. The lifecycle data suggests it's a survival adaptation worth reading carefully.
What the data shows
In instrumented Discord communities, members who muted a server but kept visiting it manually retained longer than members who left notifications on. Across one 12-month cohort, the "muted-but-active" segment had the lowest 6-month churn of any group — below even unmuted dailies.
Why it happens
Notification fatigue has a known shape: ping volume rises, the member's marginal tolerance falls, and at the breaking point they choose between muting and leaving. Muting is the cheaper exit. The member who mutes has decided to stay on their terms; the one who can't mute fast enough just leaves. Telegram's per-chat mute and granular @mention controls make this off-ramp smoother, which may partly explain its higher passive retention.
The caveat
This is a self-selected segment — muters may differ in commitment from the start. And "muted-but-active" is invisible in standard dashboards, so it's chronically under-measured.
Open question: should servers default new members to a low-noise notification tier, treating the mute as something to pre-empt rather than mourn?
Server owners treat muting as defeat. The lifecycle data suggests it's a survival adaptation worth reading carefully.
What the data shows
In instrumented Discord communities, members who muted a server but kept visiting it manually retained longer than members who left notifications on. Across one 12-month cohort, the "muted-but-active" segment had the lowest 6-month churn of any group — below even unmuted dailies.
Why it happens
Notification fatigue has a known shape: ping volume rises, the member's marginal tolerance falls, and at the breaking point they choose between muting and leaving. Muting is the cheaper exit. The member who mutes has decided to stay on their terms; the one who can't mute fast enough just leaves. Telegram's per-chat mute and granular @mention controls make this off-ramp smoother, which may partly explain its higher passive retention.
The caveat
This is a self-selected segment — muters may differ in commitment from the start. And "muted-but-active" is invisible in standard dashboards, so it's chronically under-measured.
Open question: should servers default new members to a low-noise notification tier, treating the mute as something to pre-empt rather than mourn?