Яндекс запустил сервис ПроБлогер

Яндекс запустил ПроБлогер — платформу для монетизации небольших каналов и групп во ВКонтакте, Дзене, Максе, Telegram, YouTube и Rutube. Для модерации нужны от 1000 подписчиков, свежие публикации, статус самозанятого, ИП или юрлица и соблюдение закона. Доход доступен через автопостинг с оплатой за просмотры и партнёрские ссылки; CPM можно задать самому или отдать аукциону.

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Google ads упростил перенос креативов из Asset Studio

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A 10-minute raid response runbook to write before you need it

Raids are won by what you decided in advance, not your reflexes at 3am. The communities that recover fastest have a runbook; the ones that bleed members improvise. Here's the skeleton.

Pre-stage (do today)
— Define 'raid' numerically: e.g. 20+ joins in 5 minutes from new accounts
— Pre-build a lockdown role that strips send-message perms server-wide
— Set verification level to escalate automatically on join velocity

During (first 2 minutes)
— Lockdown first, investigate second — you can always unlock
— Stop deleting messages individually; bulk-purge by join-time window

During (minutes 2-10)
— Ban by account-age and join-timestamp cluster, not by reading each
— Post one calm pinned line so regulars know it's handled

After
— Restore perms gradually, watch for a second wave (raiders test resilience)
— Log the join-velocity that triggered it to tune your threshold

Discord vs Telegram
Discord's audit log + anti-raid bots make timestamp-cluster bans fast. Telegram's coarser admin tools mean prevention (join-request approval) beats cleanup — you rarely get a clean bulk-ban.

The caveat
Over-tuned auto-lockdown punishes organic surges (a viral mention looks like a raid). Keep a human override.

Open question: does visible, fast raid handling actually retain bystanders, or do they leave regardless of how well you respond?

How to run a lapsed-member reactivation campaign that isn't spam

Reactivating dormant members is cheaper than acquiring new ones, but a clumsy 'we miss you!' ping just triggers the leave you were trying to prevent. Here's a measured approach.

Step 1: segment by lapse depth
— Recently quiet (active in last 30-60 days): light touch
— Deep dormant (60+ days silent): different message, lower expectations
Never blast both the same way.

Step 2: pick the trigger, not the calendar
Reactivate around a real event — a launch, an AMA, a resolved feature request they once asked for. Event-anchored re-engagement outperforms time-anchored 'come back' messages because it carries information, not guilt.

Step 3: measure the right outcome
Don't count opens or who saw the ping. Count members who post within 72 hours of contact, and critically, who are still active 14 days later. Most reactivation 'wins' relapse inside two weeks.

Step 4: cap frequency
One reactivation touch per quarter per member, maximum. Beyond that you're training people to mute.

The caveat
Reactivation studies from email show small uplifts (low single-digit percentages re-engage durably). Don't expect a wave — expect a trickle, and judge it against doing nothing.

Open question: is a dormant member who lurks-and-reads actually 'lapsed,' or are we measuring the wrong thing by requiring a post?

How to A/B test a bot's engagement value honestly

Every server adds engagement bots — levels, welcomes, games — and almost nobody tests whether they help or just add noise. Here's how to run a defensible experiment.

Step 1: define the outcome before you start
Not 'command usage.' A bot can be heavily used and still not move retention. Pick week-2 retention of new joiners as your primary metric.

Step 2: split by cohort, not by toggle
You can't easily A/B a single server. Instead compare consecutive join cohorts: 4 weeks with the bot's feature on, 4 weeks off, then on again. The on-off-on shape guards against a trend masquerading as an effect.

Step 3: watch for displacement
Level bots often raise message count while lowering message quality — people post '+1' to grind XP. Track median message length alongside volume.

What the evidence suggests
Level-reward systems reliably lift raw message counts; their effect on retention is mixed and often null once you control for the kind of member they attract.

The caveat
Consecutive-cohort designs are confounded by everything else changing over 12 weeks (seasonality, a viral post). Treat the result as a signal, not proof.

Open question: if a bot inflates volume but not retention, is it still worth keeping for the perceived liveliness it creates for newcomers?

Beyond the niche

Most of you wear more than one hat — @TrenchContent covers content SEO, which pairs nicely with what we do. Real tactics from someone actually shipping content every week — what's ranking…

Telegram serverless вышел в открытый бета-тест

Telegram запустил serverless-серверы для ботов, но в CPA и iGaming-задачах они полезны только для простых webhook-сценариев: приветствие, короткий диалог, выдача ссылки. Для приёма заявок, публичных URL и работы с медиа функция не подходит, поэтому практической пользы для вайт-проектов и Tg Ads почти нет.

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Компании запретили использовать название Twitter, но разрешили символику

Суд в Делавере запретил стартапу использовать бренд Twitter: посчитал, что это вводит в заблуждение и нарушает права X на товарный знак. При этом X не удалось заблокировать слово Tweet и старый логотип с птицей — суд счёл, что после ребрендинга в X эти марки фактически заброшены. Решение пока предварительное и может быть оспорено.

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ChatGPT сможет общаться вместо тебя

OpenAI тестирует Writing Style: ChatGPT сможет изучать манеру письма и отвечать в стиле пользователя в Slack, Gmail и мессенджерах. Это усиливает персонализацию и снимает рутину общения, но компания одновременно режет риск копирования узнаваемых авторских стилей, чтобы не конфликтовать с правами и IP.

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How to build a moderation shift schedule from your own activity data

Most mod teams cover whenever they happen to be online, which leaves predictable gaps — and bad actors learn your gaps faster than you do. Here's how to schedule coverage off real data.

Step 1: map activity by hour
Pull message volume by hour-of-day and day-of-week across a month. You'll find 2-3 peaks and a long quiet trough — usually overnight in your dominant timezone.

Step 2: map incidents, separately
Plot when reports, deletions, and bans actually happen. Incidents often cluster differently from chatter — frequently in the quiet hours when fewer eyes are on.

Step 3: staff the overlap
The danger window is high-incident, low-coverage. Prioritize mods there, not at peak chatter where the crowd self-polices.

Step 4: automate the trough
Where you genuinely can't staff, tighten automod thresholds for those hours rather than leaving them wide open.

Discord vs Telegram
Discord lets you scope automod by time indirectly via stricter rules; Telegram leans harder on pre-approval since live moderation across timezones is thin. Global communities suffer most — there's no 'night.'

The caveat
Incident timing is partly endogenous: bad actors strike when they sense gaps, so plugging one gap shifts the cluster. Re-measure after changes.

Open question: is round-the-clock human coverage even the goal, or should mature servers design for graceful automated degradation overnight?

Facebook начал считать успешные и провальные платежи

Meta добавила в Facebook Manager счётчик статусов платежей в billings, чтобы не проверять транзакции вручную. Для арбитражников и iGaming это почти бесполезно: нужные данные по биллингу всё равно видны в платёжке, а нововведение больше актуально для белых рекламных аккаунтов с моделью ежемесячных списаний.

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